{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importing the dependencies\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Storing the csvpaths\n",
    "csvpath_confirmed=\"time_series_19-covid-Confirmed.csv\"\n",
    "csvpath_deaths=\"time_series_19-covid-Deaths.csv\"\n",
    "csvpath_recovered=\"time_series_19-covid-Recovered.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Reading into a pandas DataFrame\n",
    "Confirmed_df1=pd.read_csv(csvpath_confirmed)\n",
    "Deaths_df1=pd.read_csv(csvpath_deaths)\n",
    "Recovered_df1=pd.read_csv(csvpath_recovered)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Manipulating the Confirmed dataframe\n",
    "#Dropping the colums which are not required\n",
    "Confirmed_df1.drop(columns=[\"Province/State\",\"Lat\",\"Long\"],inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country/Region</th>\n",
       "      <th>1/22/20</th>\n",
       "      <th>1/23/20</th>\n",
       "      <th>1/24/20</th>\n",
       "      <th>1/25/20</th>\n",
       "      <th>1/26/20</th>\n",
       "      <th>1/27/20</th>\n",
       "      <th>1/28/20</th>\n",
       "      <th>1/29/20</th>\n",
       "      <th>1/30/20</th>\n",
       "      <th>...</th>\n",
       "      <th>3/4/20</th>\n",
       "      <th>3/5/20</th>\n",
       "      <th>3/6/20</th>\n",
       "      <th>3/7/20</th>\n",
       "      <th>3/8/20</th>\n",
       "      <th>3/9/20</th>\n",
       "      <th>3/10/20</th>\n",
       "      <th>3/11/20</th>\n",
       "      <th>3/12/20</th>\n",
       "      <th>3/13/20</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Thailand</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>43</td>\n",
       "      <td>47</td>\n",
       "      <td>48</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>53</td>\n",
       "      <td>59</td>\n",
       "      <td>70</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Japan</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>331</td>\n",
       "      <td>360</td>\n",
       "      <td>420</td>\n",
       "      <td>461</td>\n",
       "      <td>502</td>\n",
       "      <td>511</td>\n",
       "      <td>581</td>\n",
       "      <td>639</td>\n",
       "      <td>639</td>\n",
       "      <td>701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Singapore</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>110</td>\n",
       "      <td>117</td>\n",
       "      <td>130</td>\n",
       "      <td>138</td>\n",
       "      <td>150</td>\n",
       "      <td>150</td>\n",
       "      <td>160</td>\n",
       "      <td>178</td>\n",
       "      <td>178</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Nepal</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>83</td>\n",
       "      <td>93</td>\n",
       "      <td>99</td>\n",
       "      <td>117</td>\n",
       "      <td>129</td>\n",
       "      <td>149</td>\n",
       "      <td>149</td>\n",
       "      <td>197</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Country/Region  1/22/20  1/23/20  1/24/20  1/25/20  1/26/20  1/27/20  \\\n",
       "0       Thailand        2        3        5        7        8        8   \n",
       "1          Japan        2        1        2        2        4        4   \n",
       "2      Singapore        0        1        3        3        4        5   \n",
       "3          Nepal        0        0        0        1        1        1   \n",
       "4       Malaysia        0        0        0        3        4        4   \n",
       "\n",
       "   1/28/20  1/29/20  1/30/20  ...  3/4/20  3/5/20  3/6/20  3/7/20  3/8/20  \\\n",
       "0       14       14       14  ...      43      47      48      50      50   \n",
       "1        7        7       11  ...     331     360     420     461     502   \n",
       "2        7        7       10  ...     110     117     130     138     150   \n",
       "3        1        1        1  ...       1       1       1       1       1   \n",
       "4        4        7        8  ...      50      50      83      93      99   \n",
       "\n",
       "   3/9/20  3/10/20  3/11/20  3/12/20  3/13/20  \n",
       "0      50       53       59       70       75  \n",
       "1     511      581      639      639      701  \n",
       "2     150      160      178      178      200  \n",
       "3       1        1        1        1        1  \n",
       "4     117      129      149      149      197  \n",
       "\n",
       "[5 rows x 53 columns]"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Filling NaN with a 0 for calculations\n",
    "Confirmed_df1=Confirmed_df1.fillna(0)\n",
    "Confirmed_df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Grouping the Confirmed cases dataframe by Country/Region\n",
    "Confirmed_group=Confirmed_df1.groupby([\"Country/Region\"])\n",
    "#Creating the final Confirmed dataframe to be used further\n",
    "Confirmed_final=Confirmed_group.sum()\n",
    "\n",
    "#Manipulating the Deaths dataframe\n",
    "#Dropping the colums which are not required\n",
    "Deaths_df1.drop(columns=[\"Province/State\",\"Lat\",\"Long\"],inplace=True)\n",
    "#Filling NaN with a 0 for calculations\n",
    "Deaths_df1=Deaths_df1.fillna(0)\n",
    "#Grouping the Death cases dataframe by Country/Region\n",
    "Deaths_group=Deaths_df1.groupby([\"Country/Region\"])\n",
    "#Creating the final Death dataframe to be used further\n",
    "Deaths_final=Deaths_group.sum()\n",
    "\n",
    "Recovered_df1.drop(columns=[\"Province/State\",\"Lat\",\"Long\"],inplace=True)\n",
    "Recovered_df1=Recovered_df1.fillna(0)\n",
    "Recovered_group=Recovered_df1.groupby([\"Country/Region\"])\n",
    "Recovered_final=Recovered_group.sum()\n",
    "#len(Confirmed_final)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>1/22/20</th>\n",
       "      <th>1/23/20</th>\n",
       "      <th>1/24/20</th>\n",
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       "      <th>1/26/20</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>8</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>Antigua and Barbuda</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "</table>\n",
       "<p>5 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     1/22/20  1/23/20  1/24/20  1/25/20  1/26/20  1/27/20  \\\n",
       "Country/Region                                                              \n",
       "Afghanistan                0        0        0        0        0        0   \n",
       "Albania                    0        0        0        0        0        0   \n",
       "Algeria                    0        0        0        0        0        0   \n",
       "Andorra                    0        0        0        0        0        0   \n",
       "Antigua and Barbuda        0        0        0        0        0        0   \n",
       "\n",
       "                     1/28/20  1/29/20  1/30/20  1/31/20  ...  3/4/20  3/5/20  \\\n",
       "Country/Region                                           ...                   \n",
       "Afghanistan                0        0        0        0  ...       0       0   \n",
       "Albania                    0        0        0        0  ...       0       0   \n",
       "Algeria                    0        0        0        0  ...       0       0   \n",
       "Andorra                    0        0        0        0  ...       0       0   \n",
       "Antigua and Barbuda        0        0        0        0  ...       0       0   \n",
       "\n",
       "                     3/6/20  3/7/20  3/8/20  3/9/20  3/10/20  3/11/20  \\\n",
       "Country/Region                                                          \n",
       "Afghanistan               0       0       0       0        0        0   \n",
       "Albania                   0       0       0       0        0        0   \n",
       "Algeria                   0       0       0       0        0        0   \n",
       "Andorra                   0       0       0       0        0        0   \n",
       "Antigua and Barbuda       0       0       0       0        0        0   \n",
       "\n",
       "                     3/12/20  3/13/20  \n",
       "Country/Region                         \n",
       "Afghanistan                0        0  \n",
       "Albania                    0        0  \n",
       "Algeria                    8        8  \n",
       "Andorra                    1        0  \n",
       "Antigua and Barbuda        0        0  \n",
       "\n",
       "[5 rows x 52 columns]"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Recovered_final.head()\n",
    "#len(Recovered_final)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Dates</th>\n",
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       "      <th>#Cumulative Death Cases</th>\n",
       "      <th>#Cumulative Recovered Cases</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>548</td>\n",
       "      <td>17</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/23/20</td>\n",
       "      <td>643</td>\n",
       "      <td>18</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/24/20</td>\n",
       "      <td>920</td>\n",
       "      <td>26</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/25/20</td>\n",
       "      <td>1406</td>\n",
       "      <td>42</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/26/20</td>\n",
       "      <td>2075</td>\n",
       "      <td>56</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Dates  #Cumulative Confirmed Cases  #Cumulative Death Cases  \\\n",
       "0  1/22/20                          548                       17   \n",
       "1  1/23/20                          643                       18   \n",
       "2  1/24/20                          920                       26   \n",
       "3  1/25/20                         1406                       42   \n",
       "4  1/26/20                         2075                       56   \n",
       "\n",
       "   #Cumulative Recovered Cases  \n",
       "0                           28  \n",
       "1                           30  \n",
       "2                           36  \n",
       "3                           39  \n",
       "4                           49  "
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "china_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"China\",:].index.tolist(),\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"China\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"China\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"China\",:].tolist()})\n",
    "china_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>#Cumulative Death Cases</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1/22/20</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/23/20</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/24/20</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/25/20</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/26/20</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Dates  #Cumulative Confirmed Cases  #Cumulative Death Cases  \\\n",
       "0  1/22/20                            1                        0   \n",
       "1  1/23/20                            1                        0   \n",
       "2  1/24/20                            2                        0   \n",
       "3  1/25/20                            2                        0   \n",
       "4  1/26/20                            5                        0   \n",
       "\n",
       "   #Cumulative Recovered Cases  \n",
       "0                            0  \n",
       "1                            0  \n",
       "2                            0  \n",
       "3                            0  \n",
       "4                            0  "
      ]
     },
     "execution_count": 207,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "US_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"US\",:].index.tolist(),\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"US\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"US\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"US\",:].tolist()})\n",
    "US_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/24/20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/25/20</td>\n",
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       "      <th>4</th>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Dates  #Cumulative Confirmed Cases  #Cumulative Death Cases  \\\n",
       "0  1/22/20                            0                        0   \n",
       "1  1/23/20                            0                        0   \n",
       "2  1/24/20                            0                        0   \n",
       "3  1/25/20                            0                        0   \n",
       "4  1/26/20                            1                        0   \n",
       "\n",
       "   #Cumulative Recovered Cases  \n",
       "0                            0  \n",
       "1                            0  \n",
       "2                            0  \n",
       "3                            0  \n",
       "4                            0  "
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "canada_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Canada\",:].index.tolist(),\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Canada\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Canada\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Canada\",:].tolist()})\n",
    "canada_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <th>#Cumulative Death Cases</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>3/9/20</td>\n",
       "      <td>7478</td>\n",
       "      <td>53</td>\n",
       "      <td>118</td>\n",
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       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>3/10/20</td>\n",
       "      <td>7513</td>\n",
       "      <td>54</td>\n",
       "      <td>247</td>\n",
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       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>3/11/20</td>\n",
       "      <td>7755</td>\n",
       "      <td>60</td>\n",
       "      <td>288</td>\n",
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       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>3/12/20</td>\n",
       "      <td>7869</td>\n",
       "      <td>66</td>\n",
       "      <td>333</td>\n",
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       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>3/13/20</td>\n",
       "      <td>7979</td>\n",
       "      <td>66</td>\n",
       "      <td>510</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Dates  #Cumulative Confirmed Cases  #Cumulative Death Cases  \\\n",
       "47   3/9/20                         7478                       53   \n",
       "48  3/10/20                         7513                       54   \n",
       "49  3/11/20                         7755                       60   \n",
       "50  3/12/20                         7869                       66   \n",
       "51  3/13/20                         7979                       66   \n",
       "\n",
       "    #Cumulative Recovered Cases  \n",
       "47                          118  \n",
       "48                          247  \n",
       "49                          288  \n",
       "50                          333  \n",
       "51                          510  "
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "southKorea_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Korea, South\",:].index.tolist(),\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Korea, South\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Korea, South\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Korea, South\",:].tolist()})\n",
    "southKorea_df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <td>200</td>\n",
       "      <td>0</td>\n",
       "      <td>97</td>\n",
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      "text/plain": [
       "      Dates  #Cumulative Confirmed Cases  #Cumulative Death Cases  \\\n",
       "47   3/9/20                          150                        0   \n",
       "48  3/10/20                          160                        0   \n",
       "49  3/11/20                          178                        0   \n",
       "50  3/12/20                          178                        0   \n",
       "51  3/13/20                          200                        0   \n",
       "\n",
       "    #Cumulative Recovered Cases  \n",
       "47                           78  \n",
       "48                           78  \n",
       "49                           96  \n",
       "50                           96  \n",
       "51                           97  "
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "singapore_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Singapore\",:].index.tolist(),\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Singapore\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Singapore\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Singapore\",:].tolist()})\n",
    "singapore_df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>17660</td>\n",
       "      <td>1266</td>\n",
       "      <td>1439</td>\n",
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       "</table>\n",
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      "text/plain": [
       "      Dates  #Cumulative Confirmed Cases  #Cumulative Death Cases  \\\n",
       "47   3/9/20                         9172                      463   \n",
       "48  3/10/20                        10149                      631   \n",
       "49  3/11/20                        12462                      827   \n",
       "50  3/12/20                        12462                      827   \n",
       "51  3/13/20                        17660                     1266   \n",
       "\n",
       "    #Cumulative Recovered Cases  \n",
       "47                          724  \n",
       "48                          724  \n",
       "49                         1045  \n",
       "50                         1045  \n",
       "51                         1439  "
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "italy_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Italy\",:].index.tolist(),\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Italy\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Italy\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Italy\",:].tolist()})\n",
    "italy_df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>3/9/20</td>\n",
       "      <td>7161</td>\n",
       "      <td>237</td>\n",
       "      <td>2394</td>\n",
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       "      <td>2731</td>\n",
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       "      <th>50</th>\n",
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       "      <td>3/13/20</td>\n",
       "      <td>11364</td>\n",
       "      <td>514</td>\n",
       "      <td>2959</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Dates  #Cumulative Confirmed Cases  #Cumulative Death Cases  \\\n",
       "47   3/9/20                         7161                      237   \n",
       "48  3/10/20                         8042                      291   \n",
       "49  3/11/20                         9000                      354   \n",
       "50  3/12/20                        10075                      429   \n",
       "51  3/13/20                        11364                      514   \n",
       "\n",
       "    #Cumulative Recovered Cases  \n",
       "47                         2394  \n",
       "48                         2731  \n",
       "49                         2959  \n",
       "50                         2959  \n",
       "51                         2959  "
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iran_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Iran\",:].index.tolist(),\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Iran\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Iran\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Iran\",:].tolist()})\n",
    "iran_df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dates</th>\n",
       "      <th>#Cumulative Confirmed Cases</th>\n",
       "      <th>#Cumulative Death Cases</th>\n",
       "      <th>#Cumulative Recovered Cases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1/22/20</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1/23/20</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1/24/20</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1/25/20</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1/26/20</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Dates  #Cumulative Confirmed Cases  #Cumulative Death Cases  \\\n",
       "0  1/22/20                            2                        0   \n",
       "1  1/23/20                            1                        0   \n",
       "2  1/24/20                            2                        0   \n",
       "3  1/25/20                            2                        0   \n",
       "4  1/26/20                            4                        0   \n",
       "\n",
       "   #Cumulative Recovered Cases  \n",
       "0                            0  \n",
       "1                            0  \n",
       "2                            0  \n",
       "3                            0  \n",
       "4                            1  "
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "japan_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Japan\",:].index.tolist(),\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Japan\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Japan\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Japan\",:].tolist()})\n",
    "japan_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [],
   "source": [
    "### MERGED TOTAL COUNTS\n",
    "###\n",
    "###\n",
    "confirmed_total_china=china_df.loc[len(china_df)-1,\"#Cumulative Confirmed Cases\"]\n",
    "#confirmed_total_china\n",
    "death_total_china=china_df.loc[len(china_df)-1,\"#Cumulative Death Cases\"]\n",
    "#death_total_china\n",
    "recovered_total_china=china_df.loc[len(china_df)-1,\"#Cumulative Recovered Cases\"]\n",
    "#recovered_total_china\n",
    "\n",
    "confirmed_total_canada=canada_df.loc[len(canada_df)-1,\"#Cumulative Confirmed Cases\"]\n",
    "death_total_canada=canada_df.loc[len(canada_df)-1,\"#Cumulative Death Cases\"]\n",
    "recovered_total_canada=canada_df.loc[len(canada_df)-1,\"#Cumulative Recovered Cases\"]\n",
    "\n",
    "confirmed_total_iran=southKorea_df.loc[len(iran_df)-1,\"#Cumulative Confirmed Cases\"]\n",
    "death_total_iran=southKorea_df.loc[len(iran_df)-1,\"#Cumulative Death Cases\"]\n",
    "recovered_total_iran=southKorea_df.loc[len(iran_df)-1,\"#Cumulative Recovered Cases\"]\n",
    "\n",
    "confirmed_total_italy=italy_df.loc[len(italy_df)-1,\"#Cumulative Confirmed Cases\"]\n",
    "death_total_italy=italy_df.loc[len(italy_df)-1,\"#Cumulative Death Cases\"]\n",
    "recovered_total_italy=italy_df.loc[len(italy_df)-1,\"#Cumulative Recovered Cases\"]\n",
    "\n",
    "confirmed_total_singapore=singapore_df.loc[len(singapore_df)-1,\"#Cumulative Confirmed Cases\"]\n",
    "death_total_singapore=singapore_df.loc[len(singapore_df)-1,\"#Cumulative Death Cases\"]\n",
    "recovered_total_singapore=singapore_df.loc[len(singapore_df)-1,\"#Cumulative Recovered Cases\"]\n",
    "\n",
    "confirmed_total_southKorea=southKorea_df.loc[len(southKorea_df)-1,\"#Cumulative Confirmed Cases\"]\n",
    "death_total_southKorea=southKorea_df.loc[len(southKorea_df)-1,\"#Cumulative Death Cases\"]\n",
    "recovered_total_southKorea=southKorea_df.loc[len(southKorea_df)-1,\"#Cumulative Recovered Cases\"]\n",
    "\n",
    "confirmed_total_US=US_df.loc[len(US_df)-1,\"#Cumulative Confirmed Cases\"]\n",
    "death_total_US=US_df.loc[len(US_df)-1,\"#Cumulative Death Cases\"]\n",
    "recovered_total_US=US_df.loc[len(US_df)-1,\"#Cumulative Recovered Cases\"]\n",
    "\n",
    "confirmed_total_japan=japan_df.loc[len(japan_df)-1,\"#Cumulative Confirmed Cases\"]\n",
    "death_total_japan=japan_df.loc[len(japan_df)-1,\"#Cumulative Death Cases\"]\n",
    "recovered_total_japan=japan_df.loc[len(japan_df)-1,\"#Cumulative Recovered Cases\"]\n",
    "\n",
    "\n",
    "\n",
    "### TOTAL POPULATIONS\n",
    "###\n",
    "###\n",
    "total_population_china = 1437677020\n",
    "total_population_southKorea = 51269185 \n",
    "total_population_singapore=5836884\n",
    "total_population_italy = 60550075\n",
    "total_population_iran = 82913906\n",
    "total_population_US = 330425304 \n",
    "total_population_canada = 37643160 \n",
    "total_population_japan = 126150000\n",
    "\n",
    "### LENGTH COUNT\n",
    "###\n",
    "###\n",
    "total_days_china = len(china_df)\n",
    "total_days_singapore = len(singapore_df)\n",
    "total_days_southKorea = len(southKorea_df)\n",
    "total_days_iran = len(iran_df)\n",
    "total_days_italy = len(italy_df)\n",
    "total_days_US = len(US_df)\n",
    "total_days_canada = len(canada_df)\n",
    "total_days_japan = len(japan_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 251,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### PERCENTAGE OF ITEMS AND INFECTION RATE EQUATIONS\n",
    "###\n",
    "###\n",
    "\n",
    "#% of Death=Total Death/Total confirmed *100\n",
    "#% of Recovered=Total Recovered/Total confirmed *100\n",
    "#Infection rate=Total confirmed/Total population *100\n",
    "#Speed of Infection=Total Confirmed/Total days\n",
    "percentage_death_china = round((death_total_china/confirmed_total_china)*100,2)\n",
    "#percentage_death_china\n",
    "percentage_recovered_china = round((recovered_total_china/confirmed_total_china)*100,2)\n",
    "#percentage_recovered_china\n",
    "infection_rate_china = round((confirmed_total_china/total_population_china)*100,5)\n",
    "#infection_rate_china\n",
    "speed_infection_china = round((confirmed_total_china/total_days_china),1)\n",
    "day_0_china = len(china_df['Dates'])-(len(china_df['Dates'])-len(china_df[china_df['#Cumulative Confirmed Cases']==0]))\n",
    "#day0\n",
    "\n",
    "percentage_death_singapore = round((death_total_singapore/confirmed_total_singapore)*100,2)\n",
    "percentage_recovered_singapore = round((recovered_total_singapore/confirmed_total_singapore)*100,2)\n",
    "infection_rate_singapore = round((confirmed_total_singapore/total_population_singapore)*100,5)\n",
    "speed_infection_singapore = round((confirmed_total_singapore/total_days_singapore),1)\n",
    "day_0_singapore = len(singapore_df['Dates'])-(len(singapore_df['Dates'])-len(singapore_df[singapore_df['#Cumulative Confirmed Cases']==0]))\n",
    "#day1\n",
    "\n",
    "percentage_death_southKorea = round((death_total_southKorea/confirmed_total_southKorea)*100,2)\n",
    "percentage_recovered_southKorea = round((recovered_total_southKorea/confirmed_total_southKorea)*100,2)\n",
    "infection_rate_southKorea = round((confirmed_total_southKorea/total_population_southKorea)*100,5)\n",
    "speed_infection_southKorea = round((confirmed_total_southKorea/total_days_southKorea),1)\n",
    "day_0_southKorea = len(southKorea_df['Dates'])-(len(southKorea_df['Dates'])-len(southKorea_df[southKorea_df['#Cumulative Confirmed Cases']==0]))\n",
    "#day0\n",
    "\n",
    "percentage_death_italy = round((death_total_italy/confirmed_total_italy)*100,2)\n",
    "percentage_recovered_italy = round((recovered_total_italy/confirmed_total_italy)*100,2)\n",
    "infection_rate_italy = round((confirmed_total_italy/total_population_italy)*100,5)\n",
    "speed_infection_italy = round((confirmed_total_italy/total_days_italy),1)\n",
    "day_0_italy = len(italy_df['Dates'])-(len(italy_df['Dates'])-len(italy_df[italy_df['#Cumulative Confirmed Cases']==0]))\n",
    "#day9\n",
    "\n",
    "percentage_death_iran = round((death_total_iran/confirmed_total_iran)*100,2)\n",
    "percentage_recovered_iran = round((recovered_total_iran/confirmed_total_iran)*100,2)\n",
    "infection_rate_iran = round((confirmed_total_iran/total_population_iran)*100,5)\n",
    "speed_infection_iran = round((confirmed_total_iran/total_days_iran),1)\n",
    "day_0_iran = len(iran_df['Dates'])-(len(iran_df['Dates'])-len(iran_df[iran_df['#Cumulative Confirmed Cases']==0]))\n",
    "#day 28\n",
    "\n",
    "percentage_death_US = round((death_total_US/confirmed_total_US)*100,2)\n",
    "percentage_recovered_US = round((recovered_total_US/confirmed_total_US)*100,2)\n",
    "infection_rate_US = round((confirmed_total_US/total_population_US)*100,5)\n",
    "speed_infection_US = round((confirmed_total_US/total_days_US),1)\n",
    "day_0_US = len(US_df['Dates'])-(len(US_df['Dates'])-len(US_df[US_df['#Cumulative Confirmed Cases']==0]))\n",
    "#day0\n",
    "\n",
    "percentage_death_canada = round((death_total_canada/confirmed_total_canada)*100,2)\n",
    "percentage_recovered_canada = round((recovered_total_canada/confirmed_total_canada)*100,2)\n",
    "infection_rate_canada = round((confirmed_total_canada/total_population_canada)*100,5)\n",
    "speed_infection_canada = round((confirmed_total_canada/total_days_canada),1)\n",
    "day_0_canada = len(canada_df['Dates'])-(len(canada_df['Dates'])-len(canada_df[canada_df['#Cumulative Confirmed Cases']==0]))\n",
    "#day 4\n",
    "\n",
    "percentage_death_japan = round((death_total_japan/confirmed_total_japan)*100,2)\n",
    "percentage_recovered_japan = round((recovered_total_japan/confirmed_total_japan)*100,2)\n",
    "infection_rate_japan = round((confirmed_total_japan/total_population_japan)*100,5)\n",
    "speed_infection_japan = round((confirmed_total_japan/total_days_japan),1)\n",
    "day_0_japan = len(japan_df['Dates'])-(len(japan_df['Dates'])-len(japan_df[japan_df['#Cumulative Confirmed Cases']==0]))\n",
    "\n",
    "day_0_japan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9+zzI6S/ROv+7tTLL99jYepw6ZX3/W1kurjJLHJVSjYAJQDutdZpSaiUwAugH/J/WerlSahFGQvix6f1PrXUrpdQI4J/AcKVUO1M9L6AhsFEp1cZ0mA+BB4HTwA6lVLjWOraszqmsxMTE4O/vX6y6TZo0YevWrUyePJmwsDB++eUX0tPT8fLyypccFmbWrFnUqlWLrKwsQkJC2Lt3LxMmTOD9998nMjISDw+PXPs/8sgjvPbaa+bEceXKlXz//fdEREQQFxfH9u3b0VozcOBAoqOj6dGjh7nu/v378fHxwdbWNl8cu3bt4t///je//fYbWmu6dOnC/fffj7u7O3FxcXz11Vd8+umnPPzww6xevZonnniCMWPG4OLiYk7CLG3fvp2YmBiaN29OfHw8R44c4euvv2bx4sX4+/vz5ZdfsmXLFsLDw5k9ezZr1qxh1qxZ9OrViyVLlnD58mU6d+7MAw88wCeffEL16tXZu3cve/fupWPHjvmOd+TIEZo2bUqNGjVu6Tr36dOHtm3b8s0333Dw4EGUUuahwBMnTmTy5MkEBQVx8uRJevfuzYEDB5g7dy4ffvghgYGBnD17Ficnp1v+nIUQQghRtWkNmZmQkZH7deJEdfbsMZbT03Nvs1wvaDkjA06duofFiyEryzhGzquo9ZyylJQuVKtmLGdnG++Wy3nfc5Zz62HttG9DlxLWz//73+3zLmH9e0shhttX1o/jsAOclFI3gOrAWaAX8Lhp+3+AGRiJ4yDTMsAqYKEyZvgYBCzXWmcAx5VSR4DOpv2OaK2PASillpv2LVHiOGkS7NlT8PasLCes5DuF8vODefNKElXBBg4cCICPjw8pKSm4urri6uqKo6Pjbd2LuHLlShYvXkxmZiZnz54lNjYWX1/fAvdv3749Fy5cICEhgcTERNzd3WnatCnz588nIiKCDh06AMa9jHFxcbkSx8Js2bKFIUOG4OzsDMDDDz/Mzz//zMCBA2nevLm5J9bPz4/4+Pgi2+vcuXOuR1I0b94cHx8fAO655x5CQkJQSuHj42NuLyIigvDwcObOnQsYs+6ePHmS6OhoJkyYAICvry/e3rf/jz7vdT548CABAQE4Ojry7LPP8tBDD9G/f38ANm7cSGzsza/z1atXSU5OJjAwkBdffJGRI0cSGhpKgwYNbjsOIYQQQhSP0et1e6/ff/fgwoXcZTdu3F4bZ8/64OxccMJnWWa9V6mztcJCVasGDg43X1lZNXFxATu7my9b29zrDg651y33uXjxCg0bOmFjY5TlvFsuF/RuawtKwYkTx2jVqgU2Nsa6jc3NV971vGVKwaFDB2jX7l5zuVLkWy5s2759e/Hz883Vdt5jFFamFOzatYOAgABy5jK09l7Ytt9++42uXbvccj1rZY0b3/bXoewSR631GaXUXOAkkAZEALuAy1rrTNNup4FGpuVGwClT3Uyl1BWgtql8m0XTlnVO5Skv6Z8QyoWXlxerVq2yus3Ozo5siz+15H3EQs5wSBsbG/NyznpmZmaR9QGOHz/O3Llz2bFjB+7u7oSFhd3SoxyGDh3KqlWrzBP7gDF0curUqTz33HOFnm9MTAzZ2dnmoao5dCH955bnZ2try40bN4qMMScBtdaG5TXLuV45MaxevZq2bdvma6+o2UpbtWrFyZMnrT5f0dp1zsjIwM7Oju3bt7Np0yaWL1/OwoUL2bx5M9nZ2WzdujVfj+KUKVN46KGHWL9+PSEhIWzatIl77rmnyGshhBBC3C20hosX4cwZSEiAbdvqEB8Pqak3X2lp1petrV+7FmROGIs3bULRf2y2szMStZyXvX3u5Rs37M2JWY0aN5M5R8fcyV1BZUePxtKxYzur2y3Xc5arVTOSHUtRUb8RHBxcnAtgqn+Q4OD6xa5vtHGS4OAWJah/nuDg4vfYOTldogSXAIA//7yGqR+jWM6cSaNVq5LFUBxlOVTVHaMHsDlwGfga6Gtl15xMwdpv5LqQcmsT+1jNOpRSo4HRAHXq1CEqKirX9po1a5onL3n7bWst3JSVlWV1iGVRcuZGycrKyjdRSkBAAKmpqSxYsICwsDDAGLKZlpaGp6cn+/fv5+LFi6Snp7Nx40Y6duxIcnIyWmtSUlJwcHAgPT2d69evm9vO2Va7du0C62dlZXHt2jWuX7+Ok5MTNjY2HD16lPXr19O1a1eSk5Nxdnbm7Nmz5gQrp107OzsGDBjACy+8QFJSEhs2bCA5OZnu3bszc+ZMBg4ciIuLCwkJCdjb21OnTh3z+datWxc/Pz+mTJnC66+/jlKKI0eOcOjQIfz9/Rk7dizjx483J3CLFy8mJSWF7Oxs8/llZ2eTkZFBcnIyGRkZ2Nvb57quycnJpKamkpmZaS7P24bWmrS0NJKTk3Nt69mzJ++99x5z585FKcUff/xB+/bt6dKlC59//jmdOnUiNjaWmJgYrl27lu/z/Mtf/sLYsWP54IMPqFatGufOnSMqKgovL69817lz586cPXuWtLQ0unfvjpeXF35+frniyLmfce/evfj6+nLs2DFatGjBuHHjiI6OZvfu3TRq1Ii80tPT833Xrcm5H7S4yru+xFA69SWG0qkvMVScGKrCOVSEGCriOWRmKpKSqnHxogOJiQ5cvOjAxYvVzMs57zduWP6q6JWvXXv7bKpVy8bRMQsHB+Pdct3DIxsHhywcHbOBDKpXt8XeXmNnl33b79evX6NmTUfs7Kxvt7PT+ZI0a9fBxcWl2NfRwyMFF5cL5vUbN4xXSsqtt1EVv093un5FiaE4ynKo6gPAca11IoBS6n/AfYCbUsrO1OvYGEgw7X8aaAKcVkrZATWBSxblOSzrFFSei9Z6MbAYoG3btjrvX0oOHDhwy5OLWOtJuh0F1Q8PD2fSpEnMmzcPR0dHPD09mTdvHq1bt2b48OEEBgbSunVrOnbsiI2NDa6uriilcHFxMQ9NrVatmrntnG2enp4F1re1tcXZ2ZlOnTrh7+9P165dadGiBUFBQTg6OuLq6sqYMWN49NFHadCgAZGRkeZ2bW1t6dy5M6mpqTRp0oTWrVsDMHjwYE6cOEFoaCgALi4uLF26NN85L1y4kBkzZtChQweqV69O7dq1effddwkICOCZZ54hJCQEgNGjRxMUFER8fLw5brjZW+jq6oqDg4N5OYerqyvVq1fHzs7OXO7i4pKrDaUUTk5OuLq65tr29ttvM2nSJAIDA9Fa4+npydq1a5k0aRJPP/00gYGB+Pn54e/vj7Ozc75ze+edd3j99dfp0qULjo6OODs789Zbb3Hfffflu845Pa4jRowgPT0drTXz5s3D1dWVjz/+mPHjxxMYGEhmZiY9evRg0aJFfPbZZ0RGRmJra0vr1q15+OGHc/Wk5nB0dDQPGS5MVFRUCf96WL71JYbSqS8xlE59iaHixFAVzqEixHCnzuHGDUhKMnoJL16ExMSby7//fgatG3HmDJw+DefP5x+K6egIjRoZw++8vY33nPWGDeHgwe0EB3emenVwcjJednY2GP0QRf86XDrX8faHipZ+DMWvLzGUTv2KEkNxlGXieBLoqpSqjjFUNQTYCUQCQzFmVn0K+Na0f7hpfatp+2attVZKhQNfKqXex5gcpzWwHaMnsrVSqjlwBmMCnZx7Jyudhg0bsnLlSqvb3nnnHd555x3zek4Pl+U9fmFhYebeyrzbCqpv+ZeKzz//3OqxX3jhBV544YV87ea0sW/fvnx1Jk6caO4lK0iNGjX49NNPrW578cUXefHFF3OVeXp6EhMTY16fMGGCOWGbMWNGrn1TTH86Cw4OzvWPKm8bixYtMrdhuc3JyYlPPvkkX1xOTk4sX77cvF7QHwGqVauW75rnyHudc9rYvn17vn09PDxYsWJFvvIFCxbkqm8taRRCCCHKg9bGMM8rV+DyZeO1dWtt4uNzJ4N5lwublsHVtS7NmhlJYPv2uZPCnHd395v3b1mTnp6Kp2dpn60Qd5eyvMfxN6XUKoxHbmQCuzF6/dYBy5VSM01l/zJV+RfwX9PkN5cwEkG01vtNM7LGmtoZr7XOAlBKPQ/8gPE4jiVa6/1ldT5CCCGEEHeDzMybvX979tTkypXciWDOckFl+acguHkzV7VqUKcOeHgY782a3Vy2fM9Zrl0bfvnll3LpXRFC5Fams6pqracD0/MUH8PKtE5a63Tg0QLamQXMslK+Hlhf8kiFEEIIIaqm1FSjVy+nl6+w5YsX4dIly9r5b3lwdgY3N6hZ03ivWxfatMldZvkeH7+LPn388fAAF5fCewaFEBVXWT+OQwghhBBClJK0tNz3Al68mHs97/L5893JyLDelp1d7l4+P7/8PX+nT++hZ08/cyJYo4Yxw+ftiIpKxuLJWEKISkoSRyGEEEKIcpKdbfTwnTsHZ8/mfj93DuLifMnKupkQpqYW3Jabm5Hs1a5tTAjj6wupqQl07NiEOnVyJ4V16hi9gUX1/kVFXaZjaTzvXAhR6UniKIQQQghRiq5fNxK8c+cc2br1ZhJoLTE8d864pzAvZ2eoXx8cHGxp0cJIAnPu/atdO/9yrVpGD2JeUVFHCQ5ukn+DEELcJkkchRBCCFFlaA0HD8KmTXU5dcpYL+5r//4mREfDtWuWD4Iv/D011TIR7JorNqWM+wHr14cGDYzHRjRocHO9fv2byzmP64uK2i0TwwghKgRJHCuIc+fOMWnSJHbs2IGDg4P5OY5t2rQps2MGBwczd+5cOnXqVOA+8+bNY/To0VSvXh2Afv368eWXX2Jra1uiY3t7e1OjRg2UUri7u/PFF1/QrFmzErVZHsLCwujfvz9Dhw7Nt23u3Ll89tln2NnZYWtry0svvcSTTz5ZDlEKIUTVlpgIGzfCjz8ar9OnAdqVQsstAXBwgOrVjZez8813V1eoVy93meV+CQkH6dnzHnMyWKeO9V5BIYSoDOS/rwpAa82QIUN46qmnzM8J3LNnD+fPny/TxPFWzJs3jyeeeMKcOK5fb0xim/Mcx5KIjIzEw8OD6dOnM3PmzAKf63inZWZmYlfCn+yLFi3ixx9/ZPv27dSoUYMrV66wZs2aUopQCCHubmlpsGXLzURxzx6j3N0dQkLgwQfB3n4H3bsHoBTFfu3Y8TOhod2LnexFRZ0jOPie0jtxIYQoRzblHYAwEih7e3vGjBljLvPz86N79+5ERUXRv39/c/nzzz/PsmXLAOOh9a+++irdunWjU6dO/P777/Tu3ZuWLVuyaNEigELrWxo7diydOnXCy8uL6dONJ6jMnz+fhIQEevbsSc+ePc3HvHjxIm+88QYfffSRuf6MGTN47733AHj33XcJCAjA19fX3FZhunXrxpkzZ8zrS5cupXPnzvj5+fHcc8+RlZUFwPfff0/Hjh1p3749AwYMAODSpUsMHjwYX19funbtyt69e8nOzsbT05PLFk8TbtWqFefPnycxMZFHHnmEgIAA7r//fn755Rdz/KNHjyY0NJQnn3ySrKwsXn75ZfN5fPLJJ4CR5D///PO0a9eOoUOHcuHCBavnNHv2bD766CNq1KgBQM2aNXnqqacAeOuttwgICMDb25sJEyagtTZf73bt2uHr68uIESMAuHbtGs888wwBAQF06NCBb7/9FoD9+/fTuXNnAgMD8fX1JS4ursjrLIQQlVV2tpEcvvsuhIYa9/OFhsK8ecYELzNnwvbtRs/j11/D6NHQvPk1WrWCli2hRQto3hw8PY3nBjZtCk2a3HyAfMOGN4eK1qtnDCetUweqV8+SHkIhhDCR/w4rgJiYGPz9/YtVt0mTJmzdupXJkycTFhbGL7/8Qnp6Ol5eXrkS0aLMmjWLWrVqkZWVRUhICHv37mXChAm8//775p5BS4888givvfYa48aNA2DlypV8//33REREEBcXx/bt29FaM3DgQKKjo+nRo0eBx/7+++8ZPHgwAAcOHGDFihX88ssv2NvbM27cOJYtW0bfvn0ZNWoU0dHRNG/enBMnTgAwffp0OnTowJo1a9i8eTNPPvkke/bsYdCgQXzzzTc8/fTT/Pbbb3h6elKvXj0ef/xxJk+eTFBQELGxsTzyyCMcOHAAgF27drFlyxacnJxYvHgxNWvWZMeOHWRkZBAYGEhoaM+zQiEAACAASURBVCi7d+/m0KFD7Nu3j6NHj9K5c2eeeeaZXOeTnJxMcnIyLVu2tHq+zz//PG+88QYAI0aMYO3atQwYMIA5c+Zw/PhxHBwczEnvrFmz6NWrF0uWLOHy5ct07tyZBx54gEWLFjFx4kQGDhyIg4ODObkWQoiqIjHRgX//2+hR3LjRSAoBvLxgzBijV7FHj5v3AgohhChbkjjmMen7Sew5t6fA7VlZWbd9f59ffT/m9ZlX0tCsGjhwIAA+Pj6kpKTg6uqKq6srjo6OuXrcirJy5UoWL15MZmYmZ8+eJTY2Fl9f3wL3b9++PRcuXCAhIYHExETc3d1p2rQp8+fPJyIigg4djAcGp6SkEBcXZzVx7NmzJ+fPn6du3brMnDkTgE2bNrFr1y4CAgIASEtLo27dumzbto0ePXrQ3PQgqFq1agGwZcsWVq9eDUCvXr1ISkriypUrDB8+nLfeeounn36a5cuXM3z4cAA2btxIbGwsANnZ2Vy9etU87HbgwIE4OTkBEBERwd69e1m1ahUAV65cIS4ujujoaB577DFsbW1p0KABvXr1yndeWmtUIfObR0ZG8s4775CamkpSUhJ+fn4MGDAAX19fRo4cyeDBg82JdEREBOHh4cydOxeA9PR0Tp48Sbdu3Zg1axZHjx7lscceo3Xr1gUeTwghKoobN4xHSpw/DxcuGO+Wy5ZlCQndAKMHMDTUeD3wgNE7KIQQ4s6TxLEC8PLyMicoednZ2ZGdnW1eT09Pz7XdwcEBABsbG/NyznrOvXqF1Qc4fvw4c+fOZceOHbi7uxMWFmZ1v7yGDh3KqlWrOHfunHlopdaaqVOn8txzzxVZPzIyEmdnZ8LCwnjjjTd4//330Vrz1FNP8Y9//CPXvuHh4VaTsZxhnpaUUnTr1o0jR46QmJjImjVreP311wEjWdy6dStOTk4kJyfj6upqrufs7Jyr3QULFtC7d+9cba9fv77QpBCgRo0aODs7c+zYMVq0aJFrW3p6OuPGjWPnzp00adKEqVOnmq/1unXriI6OJjw8nLfffpv9+/ejtWb16tW0bds2Vzv33nsvXbp0YfXq1fTu3ZvPPvvMahIrhBBlSWu4etXoDbxwIffr999b8fHHuZPCpCTr7Tg43Bwi2rCh8SB6R8cjjBnTCh+fop81KIQQouxJ4phHUT2DeZON0tCrVy9effVVPv30U0aNGgXAjh07SE1NpUWLFsTGxpKRkUF6ejqbNm0qdBbUvJo1a1Zk/atXr+Ls7EzNmjU5f/48GzZsME/97erqSnJycr6hqmAMsxw1ahQXL17kp59+AqB3795MmzaNkSNH4uLiwpkzZ7C3t6du3bpW43NycmLevHn4+Pjw+uuvExISwqBBg5g8eTJ169bl0qVLJCcn061bN8aPH8/x48dp3rw5ly5dwtXVlR49erBs2TKmTZtGVFQUHh4e5vsKhwwZwosvvsi9995L7dq1AQgNDWXhwoW8/PLLgDEJkZ+fX764evfuzccff0yvXr2wt7fn8OHDNGrUiB49evDJJ5/w5JNPcu7cOSIjI3n88cfz1Z86dSrjx49nxYoV1KhRg6tXr7J8+XKGDRsGgIeHBykpKXz77bcMGzaM7OxsTp06Rc+ePQkKCuLLL78kJSWF3r17s2DBAhYsWIBSit27d9OhQwdzUjp27FgSEhLYu3evJI5CiFJhPH/QgZ078yeD1hLE69ett+PsXJ9GjYxksF07CA6+mRzmfa9RI39yGBV1Gl/fVmV+vkIIIW6NJI4VgFKKb775hkmTJjFnzhwcHR3Nj+No0qQJw4YNw9fXl9atW5uHgN6qW6nfvn17OnTogJeXFy1atCAwMNC8bfTo0fTt25cGDRoQGRmZq56XlxfJyck0atSIBg0aAEZiduDAAbp1M4YYubi4sHTp0gITR4AGDRrw2GOP8eGHHzJt2jRmzpxJaGgo2dnZ2Nvb8+GHH9K1a1cWL17Mww8/THZ2NrVr12bz5s3MmDGDp59+Gl9fX6pXr85//vMfc7vDhw8nICCAzz//3Fw2f/58xo8fj6+vL9evXyc4ONg8kZClZ599lvj4eDp27IjWmjp16rBmzRqGDBnC5s2b8fHxoUWLFtx///1Wz2ns2LGkpKQQEBCAvb099vb2vPTSS7i5uTFq1Ch8fHzw9PSkY8eOgDEE+oknnuDKlStorZk8eTJubm5MmzaNSZMm4evri9YaT09P1q5dy4oVK1i6dCm2trY0bNjQfM+kEELk0BpSUoyhoUlJBb/nLTMGQXTL156jo5Ho1aljTCLj62skfTkTyeQs56xv3bpFnj8ohBBViCSOFUTDhg1ZuXKl1W3vvPMO77zzjnk95568+Ph4c1lYWBhhYWHmdcttBdWPiooyl1kmV5ZeeOEFXnjhhXzt5rSxb9++fHUmTpzIxIkTrbaXIyYmJlfP7YIFC8zLw4cPN9+TaKlv37707ds31/Fr1aplnmk0r06dOuUbyurh4cGKFSvMbeTEMGPGjFz72djYMHv2bGbPnp2v3YULF+arn5dSildeeYVXXnkl37aZM2ea7+m0bGPLli359nVycjLP6Gpp6tSpTJ06tUx6wIUQldOhQ8aMot99B0eOdCM52bin0BqljJlJa9cGDw9jltEOHYzl2rUhKekQPXq0zZUQOjvLkFEhhLibSeIohBBCVFIHDhjJ4tdfQ0yMUdatG3TrloS3d0NzIpj33c0NCpvnLSrqLMHBbQveQQghxF1HEkchhBCiktAa9u+HVauMZDE21ugFDAqCDz6ARx4xnksYFXWY4GCZflQIIUTpkcRRCCGEqMC0NnoTc3oWDx40ksUePWDBAnj4YXlEhRBCiLIniaMQQghRwWgNf/xxs2fx8GGwsYH774cJE2DIEGOCGiGEEOJOkcRRCCGEqCD27oVPP23OqFFw5IiRLPbsCS++CIMHG7OaCiGEEOVBEkchhBCiHJ06BV9+CUuXGkNSbWyaEhICr7xiJIt16pR3hEIIIQTYlHcAwnDu3DlGjBhBy5YtadeuHf369ePw4cNleszg4GB27txZ6D7z5s0jNTXVvN6vXz8uX75c4mN7e3vj4+ODj48P7dq14/XXXycjI6PY7Vk+NiM+Ph5vb+8SxyiEEGXl8mX47DMIDjYehTFlCri6wocfwurVvxIRAaNGSdIohBCi4pDEsQLQWjNkyBCCg4M5evQosbGxzJ49m/Pnz5d3aPkSx/Xr1+Pm5lYqbUdGRrJv3z62b9/OsWPHGD16dLHbsva8RSGEqEjS0+F//zMms6lXz0gMz56Ft94yhqX++iuMGwdubgU8fFEIIYQoR5I4VgCRkZHY29szZswYc5mfnx/du3cnKiqK/v37m8uff/55li1bBoCnpyevvvoq3bp1o1OnTvz+++/07t2bli1bsmjRIoBC61saO3YsnTp1wsvLi+nTpwMwf/58EhIS6NmzJz179jQf8+LFi7zxxht89NFH5vozZszgvffeA+Ddd98lICAAX19fc1uFcXFxYdGiRaxZs4ZLly4V2sbgwYPx9/enc+fOLF68GIApU6aQlpaGn58fI0eOBCArK4tRo0bh5eVFaGgoaWlp5nNq164dvr6+hIWFFRmbEEKURHY2REUZSWL9+sbjMnISxB07jBlSp02Dli3LO1IhhBCicGWWOCql2iql9li8riqlJimlaimlflRKxZne3U37K6XUfKXUEaXUXqVUR4u2njLtH6eUesqi3F8ptc9UZ75SSpXV+ZSlmJgY/P39i1W3SZMmbN26le7duxMWFsaqVavYtm0bb7zxxm21M2vWLHbu3MnevXv56aef2Lt3LxMmTKBhw4ZERkYSGRmZa/9HHnmEFStWmNdXrlzJo48+SkREBHFxcWzfvp09e/awa9cuoqOjizx+jRo1aN68OXFxcYW2sWTJEnbt2sVPP/3E/PnzSUpKYs6cOTg5ObFnzx5zUhwXF8f48ePZv38/bm5urF69GoA5c+awe/du9u7dy7x5827rGgkhxK3atw/+/nfw9DQmt/nqKxg4EH74AU6fhv/7P+jUyXishhBCCFEZlNnkOFrrQ4AfgFLKFjgDfANMATZprecopaaY1v8O9AVam15dgI+BLkqpWsB0oBOggV1KqXCt9Z+mfUYD24D1QB9gQ4kCnzQJ9uwpcLNTVhbY2t5em35+UEZJysCBAwHw8fEhJSUFV1dXXF1dcXR0vK17EVeuXMnixYvJzMzk7NmzxMbG4uvrW+D+7du358KFCyQkJJCYmIi7uztNmzZl/vz5RERE0KFDBwBSUlKIi4ujR48eRcagtQYgIiKiwDbmz5/PN998Q3Z2NqdOnSIuLo7atWvna6t58+b4+fkB4O/vT3x8PAC+vr6MHDmSwYMHExIScsvXRwghinL+PHzxBSxa1Iljx4wfFX36wD//aSSNzs7lHaEQQghRfHdqVtUQ4KjW+oRSahAQbCr/DxCFkTgOAr7QRvawTSnlppRqYNr3R631JQCl1I9AH6VUFFBDa73VVP4FMJiSJo7lwMvLi1WrVlndZmdnR3Z2tnk9PT0913YHBwcAbGxszMs565mZmUXWBzh+/Dhz585lx44duLu7ExYWZnW/vIYOHcqqVavME/uAkfxNnTqV5557rsj6lpKTk4mPj6dNmzYFthEVFcXGjRvZunUrWVlZDBgwoMA4La+Fra2teajqunXriI6OJjw8nDfffJMDBw5gZyeTCwshiicrCyIijIluwsMhMxPuvTebhQth2DCZ3EYIIUTVcad+Yx4BfGVarqe1PgugtT6rlKprKm8EnLKoc9pUVlj5aSvlJVNEz2BacjKurq4lPoylXr168eqrr/Lpp58yatQoAHbs2EFqaiotWrQgNjaWjIwM0tPT2bRpE506dbrltps1a1Zk/atXr+Ls7EzNmjU5f/48GzZsIDg4GABXV1eSk5Px8PDI1/aIESMYNWoUFy9e5KeffgKgd+/eTJs2jZEjR+Li4sKZM2ewt7enbt26+ernSElJYdy4cQwePBh3d/cC27hy5Qru7u5Ur16dXbt2sW3bNnMb9vb23LhxA3t7+wKPk9NL2bNnT4KCgli2bBkpKSmlNtmPEOLuER8P//43LFliDD318ICJE+Gvf4Xz5383/x8qhBBCVBVlnjgqpaoBA4GpRe1qpUwXo9xaDKMxhrRSp04doqKicm2vWbMmycnJRYRnyMrKuuV9b6f+f//7X6ZMmcLs2bNxdHSkadOmzJkzBzc3NwYPHoy3tzctW7bEx8eH7OxskpOT0VqTkpKCg4MD6enpXL9+3dx2zrbatWsXWD8rK4tr167RsWNHvL29uffee/H09KRLly6kp6eTnJzMk08+Se/evalfvz7r1q0zt2tnZ0fTpk25cuUK9evXx8XFheTkZLp168bDDz9Mly5dAHB2dubTTz/Fyckp1/lqrbn//vvRWpOdnc2AAQN45ZVXCm0jMDCQhQsX4u3tTatWrQgICCA1NZXk5GTCwsLw9vamffv2vPHGG+ZzBMjIyCAjI4PLly/z2GOPcfXqVbTWjB07Fltb22J/niX9LpRGG4XVT09Pz/ddtyYlJeWW9quo9SWG0qkvMRRd//p1xa+/erBuXQN27XIHICDgEs8+e5b77kvC3l5z/nz5n0NptFEVYqgK51ARYqgK51ARYqgK5yAxlE79ihJDsWity/SFMQQ1wmL9ENDAtNwAOGRa/gR4LO9+wGPAJxbln5jKGgAHLcpz7VfQq02bNjqv2NjYfGUFuXr16i3vWxb1JYbSqX83xHCr3+vIyMgSxVDe9SWG0qkvMRRcf/9+rV98UWsPD61B6yZNtJ4xQ+sTJ+5cDHe6jaoQQ1U4h4oQQ1U4h4oQQ1U4B4mhdOpXlBiAnfo287o78TiOx7g5TBUgHMiZGfUp4FuL8idNs6t2Ba5oY0jrD0CoUsrdNANrKPCDaVuyUqqraTbVJy3aEkIIIYrt2jVjKGpgIHh5wYIFEBwM338Px4/D9OnQtGl5RymEEELcOWU6VFUpVR14ELCc5WQOsFIp9VfgJPCoqXw90A84AqQCTwNorS8ppd4Gdpj2e0ubJsoBxgKfA04Yk+JUuolxhBBCVAxaw8GDrnz1lfH4jORkuOcemDsX/vIXKORWbSGEEKLKK9PEUWudCtTOU5aEMctq3n01ML6AdpYAS6yU7wS8SyVYIYQQd6XERFi61Ohh3LfPHycnGD4cnn0W7rtPnrUohBBCwJ2bVbXC01qj5LcDUUVobXWeKCGESWYm/PCDMSvqd9/BjRvQuTNMnnyI6dPbUrNmeUcohBBCVCx34h7HCs/R0ZGkpCT5ZVtUCVprkpKScHR0LO9QhKhwDh+GqVON+xP794eff4YJEyAmBn77DQYOPCtJoxBCCGGF9DgCjRs35vTp0yQmJha5b3p6eol+IS9pfYmhdOpX9RgcHR1p3LhxSUITospIToavvzaGom7ZAra20K8fPPMMPPQQFPL4VyGEEEKYSOKI8fD45s2b39K+UVFRdOjQodjHKml9iaF06ksMQlRtWsMvvxhDUVeuNGZJbdsW/vlPY6KbBg3KO0IhhBCicpHEUQghRJVx8WI15swxEsa4OHBxgcceg6efhm7dZKIbIYQQorgkcRRCCFHpaQ1/+xvMm9eN7Gzo0QNeew2GDgVn5/KOTgghhKj8JHEUQghR6X3wAbz/PvTpc4758xvQunV5RySEEEJULTKrqhBCiEptwwZ46SUYMgRefvmQJI1CCCFEGZDEUQghRKV14ACMGAG+vvDf/4KN/FQTQgghyoT8iBVCCFEpJSXBgAHg5ATh4XIvoxBCCFGW5B5HIYQQlc7168bEN6dPQ1QUNGlS3hEJIYQQVZskjkIIISoVreGFF4yEcelS6Nq1vCMSQgghKodr16+x9fTWYtWVxFEIIUSlsmABLF4MU6fCyJHlHY0QQghRcf2Z9idbTm4h+kQ0P5/8mV1nd5GZnVmstiRxFEIIUWn88ANMngyDBsHMmeUdjRBCCFGxnE0+y88nfyb6RDTRJ6KJuRCDRlPNthqdG3XmlfteoXuz7vSd0fe225bEUQghRKVw8CAMHw7e3sYQVZlBVQghxN1Ma0385Xhzkhh9Mpojl44A4GzvTGDTQIZ5DaNHsx50btQZRzvHEh1PEkchhBAV3qVLxgyqDg7GDKouLuUdkRBCCHFnZetsDiQeIDwhnMWrFxN9IpozyWcAqOVUi+5NuzPGfww9mvWgQ4MO2NmUbqoniaMQQogK7cYNePRROHkSIiOhWbPyjkgIIYQoe+mZ6exM2MmWk1vYcnILv576lT/T/wSgoWtDejTrQY+mPejerDvt6rTDRpXtUBxJHIUQQlRoEyfC5s3wn//AffeVdzRCCCFE2UhKTeLXU7/yy6lf2HJyCzsSdnA96zoA93rcy9B2QwlsEojdWTse7/M4Sqk7Gp8kjkIIISqsDz+Ejz+GV16BJ58s72iEEEKI0pFzf2JOb+KWU1uITYwFwN7Gnk4NOzGxy0SCmgZxX5P78KjuYa4bdTnqjieNIImjEEKICurHH43exgEDYPbs8o5GCCGEKD6tNYeSDrHx2EZWx67m8O+HSUhOAKCmQ00CmwbyhM8TBDYNJKBhAE72TuUccX6SOAohhKhwDh+GYcOgXTtYtgxsbcs7IiGEEOL2JKUmsen4JiKORhBxNIJTV08BUM+hHiFtQghqEkRQ0yC86nqV+f2JpUESRyGEEBXKn38avYz29sYMqq6u5R2REEIIUbTrWdf59dSv/Hj0RyKORbArYRcajZujGyHNQ3it+2s82PJBTv5xkuDg4PIO97aVaeKolHIDPgO8AQ08AxwCVgCeQDwwTGv9pzIG6n4A9ANSgTCt9e+mdp4CXjc1O1Nr/R9TuT/wOeAErAcmaq11WZ6TEEKIspOZqRg2DI4fNybE8fQs74iEEEII67TWHLx4kIijEfx47Eei4qO4duMatsqWbk268Wbwm4S2DMW/oX+uR2Oc5GQ5Rl18Zd3j+AHwvdZ6qFKqGlAdeBXYpLWeo5SaAkwB/g70BVqbXl2Aj4EuSqlawHSgE0byuUspFa61/tO0z2hgG0bi2AfYUMbnJIQQoox8+GErNm6Ef/8bgoLKOxohhBAitys3rrA8Zrk5WTx99TQArWu1JswvjNCWoQR7BlPDoUY5R1r6yixxVErVAHoAYQBa6+vAdaXUICDYtNt/gCiMxHEQ8IWpx3CbUspNKdXAtO+PWutLpnZ/BPoopaKAGlrrrabyL4DBSOIohBCV0scfw5o1jfjb3yAsrLyjEUIIIeBK+hV+Pvkzm49vJjI+kj/O/YFG4+7oTkiLEEJbhPJgywfxdPMs71DLnCqrkZ1KKT9gMRALtAd2AROBM1prN4v9/tRauyul1gJztNZbTOWbMBLKYMBRaz3TVD4NSMNIOOdorR8wlXcH/q617m8lltEYPZPUqVPHf+XKlcU+r5SUFFxcXMqtvsRQOvUlhooTQ1U4h4oQQ2U/h3PnHHjiiS506JDInDkHij0Zzt1+HSWG0qsvMZROfYmhdOpLDHcuhrSsNGKuxLDn8h5+v/w7h5MPk0029soe75reeFX34r5699HGtQ22qng/rCrCdezZs+curXWn26qktS6TF8bQ0kygi2n9A+Bt4HKe/f40va8DgizKNwH+wMvA6xbl04CXgABgo0V5d+C7ouJq06aNLonIyMhyrS8xlE59iaHixFAVzqEixFDZz2HWLK1B66++2lpuMZRGfYmh4sRQFc6hIsRQFc6hIsRQFc6hqsaQdiNNRx6P1G9sfkMHLQnS9m/Za2ag7d6y04H/CtTTNk/Tm49t1mk30krl+KXRRmnEAOzUt5nfleU9jqeB01rr30zrqzDuZzyvlGqgtT5rGop6wWL/Jhb1GwMJpvLgPOVRpvLGVvYXQghRiWhtPHIjMBDq108v73CEEEJUYZnZmWw9tZXNxzezOX4zv576lfTMdGyUDf4N/JncdTK9mvcisGkgLtVK1qtX1ZRZ4qi1PqeUOqWUaqu1PgSEYAxbjQWeAuaY3r81VQkHnldKLceYHOeKKbn8AZitlHI37RcKTNVaX1JKJSulugK/AU8CC8rqfIQQQpSNP/6A2Fj46KPyjkQIIURVk62z2Xd+H5uOb2LjsY1EHY8i7ec0AHzr+TLGfwy9mveie7PuuDm6FdHa3a2sZ1V9AVhmmlH1GPA0YAOsVEr9FTgJPGradz3GoziOYDyO42kAU4L4NrDDtN9b2jRRDjCWm4/j2IBMjCOEEJXOsmVgZwePPgoxMeUdjRBCiMru+J/H2XhsI5uOb2Lz8c0kpiYC0LZ2Wx6s9yB/CfwLwZ7BeFT3KOdIK5cyTRy11nsw7nXMK8TKvhoYX0A7S4AlVsp3YjwjUgghRCWUlQVffQV9+oCH/PwWQghRDInXEtl8fLO5V/H45eMANHBpQJ9WfQhpHkJIixAa12hMVFQUwe2CyzfgSqqsexyFEEKIAkVHw5kzMHdueUcihBCiski5nsLPJ342J4p/nP8DgJoONQn2DGZy18k80OIB7vG4B6VUOUdbdUjiKIQQotwsWwYuLjBwYHlHIoQQoiKLTYxlVewqVu9ZzYGfD3Aj+wbVbKsR2CSQWb1mEdI8BP+G/tjZSHpTVuTKCiGEKBfp6bBqFQwZAtWrl3c0QgghKpqjl46yYv8KlscsZ9+FfSgUbVzb8GK3F3mgxQMENgnEyd6pvMO8a0jiKIQQolxs2ABXrsDIkeUdiRBCiIri9NXTrNy/kuUxy9mRYMyNGdQ0iIV9FzK03VAO7DxAcHBw+QZ5l5LEUQghRLlYtgzq1oWQfNOlCSGEuJtcuHaBVbGrWB6znJ9P/gyAfwN/3n3wXYZ7DadJzZuPej/AgfIK864niaMQQog77soVWLsWnnvOeBSHEEKIu8ufaX/yzcFvWB6znE3HN5Gts2lXpx1v93yb4V7DaV27dXmHKPKQH9dCCCHuuNWrISNDhqkKIcTdJC0rjS/3fcnymOV8f+R7bmTfoKV7S6YGTWWE9wi868pT9ioySRyFEELcccuWQcuWEBBQ3pEIIYQoS+dSzrE+bj1rD69l/eH1ZGRn0LhGYyZ0mcAI7xH4N/CXR2ZUEpI4CiGEuKPOnIHISJg2DeR3BSGEqFq01uw+t5u1h9ey9vBa8wQ3jWs0pk/9PrwU+hKBTQOxUTblHKm4XZI4CiGEuKOWLwetZZiqEEJUFdeuX2PT8U2sPbyWdXHrSEhOQKHo2rgrs3rNon+b/vjU9eGnn36ie7Pu5R2uKCZJHIUQQtxRy5ZBp07Qpk15RyKEEKK4Tlw+wbq4daw9vJbNxzeTkZVBDYca9G7Zm/5t+tO3VV/qONcp7zBFKZLEUQghxB1z4ADs3g3/93/lHYkQQojbkZWdRcyVGCI2RbD28Fr2XdgHQKtarRgXMI7+bfoT1DSIarbVyjlSUVYkcRRCCHHHLFsGNjYwYkR5RyKEEKIoKddT+PHoj3x76FvWHl5LUloSdjZ2dG/anfdC36N/m/60qS3DR+4WkjgKIYS4I7SGL7+EkBCoX7+8oxFCCGHN2eSzfHf4O8IPhbPx2EYysjJwd3TnoTYP0eJGCyYPnIybo1t5hynKgSSOQggh7oht2+D4cZg+vbwjEUIIkUNrTWxiLN8e+pbwQ+H8P3v3HV1Ftbdx/LsTQigBEiAQOqF3kC6oFEXBQlEQK4peyxW96nvtXcFr4do7KohXlCIiqCAiEEEB6UiXEkqoAUIa6dnvHzNAgAABcjIn4fmsNWtm9sye8wxiOL/MzJ4/d/wJQGRoJP9s+0/6NOpD5xqdCQoMIioqSkXjeUyFo4iIFIgxY6BECejXz+skIiLnt8zsTP7Y9seRYnFT3CYA2lVtx7Buw+jTqA9Nw5vq/YpyDBWOIiLicxkZMG4c9O4NZct6nUZE5PyTmhwf+wAAIABJREFUkpXCxDUTmbx+Mj9t+IkDKQcoHlicSyMv5dFOj3JNw2uoWqaq1zHFj6lwFBERn5sxA/bt07sbRUQKkrWWBTELeG/he3y7+lsybAblS5bnqvpX0adhHy6vezllgst4HVMKCRWOIiLic2PGQFgY9OzpdRIRkaIvNTOVcavG8d7C91iyawllg8tydZWrebDHg3Su2ZliASoB5Mzpb42IiPhUUhJ8/z3ccgsU1+u9RER8JiYhho8Xf8yIJSOIPRRL44qN+fDKD7m15a0snreYLrW7eB1RCjEVjiIi4lOTJ8OhQ7pNVUTEF6y1/L7td95b+B7frf2ObJtN74a9eaD9A3SP7K4BbiTf+LRwNMZsARKBLCDTWtvWGFMeGAfUBrYA11tr44zzt/od4ErgEHC7tXape5zbgGfcww6z1o5229sAXwAlganAg9Za68tzEhGRMzNmDNSoARdd5HUSEZGiIyUjha9Xfs17C99jxZ4VhJUI4+GOD3Nfu/uIDIv0Op4UQQVxxbGbtXZfjvUngJnW2leNMU+4648DvYD67tQB+Ajo4BaazwNtAQssMcZMsdbGufvcDSzAKRx7AtMK4JxERCQP9u6FX36BRx6BgACv04iIFH5bD27lw0Uf8tmyzziQcoDmlZoz4uoR3NziZkoFlfI6nhRhXtyq2gfo6i6PBqJwCsc+wJfuFcMFxphQY0wVd98Z1toDAMaYGUBPY0wUUNZaO99t/xLoiwpHERG/MX48ZGXpNlURkXNhrWVZ3DLeGfcOU9ZPwWDo26gvD7R/gEtqXaLbUaVA+LpwtMAvxhgLfGKtHQFUttbuArDW7jLGVHL3rQZsz9E3xm07VXtMLu0iIuInxoyB5s2dSUREzkxmdibjV4/ntT9e4689f1GhZAUe7/w4/2z7T2qUq+F1PDnPGF8+EmiMqWqt3ekWhzOAB4Ap1trQHPvEWWvDjDE/Aa9Ya39322cCjwHdgWBr7TC3/VmcZyDnuPtf5rZfDDxmrb0mlxx349zSSnh4eJvx48ef9TklJSUREhLiWX9lyJ/+yuA/GYrCOfhDBn88h507S3DzzR25++5N3Hjj9lP09F2Ggu6vDP6ToSicgz9kKArn4A8ZzrR/enY6P+/+mXHbx7EzdSe1StWib3hfrqx5JcUDzm546qLw5+gPGYrCOQB069ZtibW27Rl1stYWyAS8ADwCrAequG1VgPXu8ifAjTn2X+9uvxHnaiU593O3rcvRfsx+J5saNGhgz8Xs2bM97a8M+dNfGfwnQ1E4B3/I4I/nMHSotWDt1q3eZSjo/srgPxmKwjn4Q4aicA7+kCGv/RNSE+zwP4bbKv+tYnkB2/7T9vb7td/brOwsz88hP45RFDIUhXOw1lpgsT3Des5nQxUYY0obY8ocXgYuB1YBU4Db3N1uAya7y1OAQcbREYi3zi2t04HLjTFhxpgw9zjT3W2JxpiO7oisg3IcS0REPGStc5vqJZdAzZpepxER8W/7D+3n+dnPU+vtWjw641GahDdh5qCZLLhzAX0a9SHAaHQx8Z4vn3GsDExyH9YtBnxtrf3ZGLMIGG+MuRPYBgxw95+K8yqOjTi3og4GsNYeMMYMBRa5+71k3YFygH9y9HUc09DAOCIifmHZMli3Dh5+2OskIiL+a0fCDt6Y/wYjlowgOSOZfo368eRFT9KuWjuvo4mc4LSFozHmdWAYkAL8DLQEHrLWfnWqftbaze6+x7fvBy7Npd0CQ05yrJHAyFzaFwPNTncOIiJSsMaMgaAg6N/f6yQiIv5nw/4NvP7H64xeMZpsm81NzW/i8c6P07RSU6+jiZxUXq44Xm6tfcwY0w9n5NIBwGzglIWjiIicn7Ky4JtvoFcvKF/e6zQiIv5j+e7lvPr7q0xYM4GggCDuan0Xj3Z+lNqhtb2OJnJaeSkcg9z5lcA37q2jPowkIiKFWVQU7NqldzeKiBy2Mn4lw78eztQNUylTvAyPdnqUhzo+RERIhNfRRPIsL4XjD8aYdTi3qt5njAkHUn0bS0RECqsxY6BMGbjmhJcjiYicP6y1/Lr5V4bNHcacrXOoWKoiw7oNY0j7IYSWCD39AUT8zGkLR2vtE8aY14AEa22WMeYQ0Mf30UREpLBJTYWJE+Haa6FkSa/TiIgUPGstP/z9A8PmDGPRzkVUK1ONIXWH8PrA1ykVVMrreCJn7bRj+xpjSuEMWvOR21QVOLOXRYqIyHnhxx8hIUG3qYrI+ScrO4txq8bR6pNW9Bnbh32H9vHJ1Z+w6V+b6F+9v4pGKfTycqvqKGAJ0MldjwEmAD/6KpSIiBROY8ZARAR07+51EhGRgpGRlcHXK7/mP7//h7/3/02jio34su+X3Nj8RooF+PLNdyIFKy9/m+taawcaY24EsNamGI2OIyIix0lMLMbUqXDffRAY6HUaERHfSs1M5YvlX/DaH6+x5eAWWlZuyYQBE+jXqB+BAfohKEVPXgrHdGNMScACGGPqAmk+TSUiIoXOnDnhpKfrNlURKdqS05MZsWQE/53/X3Ym7qRDtQ681+s9rqp/Fbq2IkVZXgrH54GfgRrGmDFAZ+B2X4YSEZHC59dfK9GgAbRp43USEZH8F58az4eLPuTNBW+y79A+utXuxpd9v6R7ZHcVjHJeyMuoqjOMMUuBjoABHrTW7vN5MhERKTRiYmDFilBeeAH0/UlEipL9h/YzMnokUxZMIT4tnl71evH0xU/TuWZnr6OJFKjTFo7GmM7AcmvtT8aYW4CnjDHvWGu3+j6eiIh4ITUVDhxwpri4o8sna9u5E6w13HST18lFRPLH/kP7eXP+m7y78F2S0pO4tvG1PHXRU7Spqtsq5PyUl1tVPwJaGmNaAo8CI4EvgS6+DCYiIr6XlgZTpjijof71V1vS0pyiMCXl5H0CA6F8eQgLc+aVK0PjxlCu3Ebq1atXcOFFRHwgZ8GYnJ7MgKYD6FmyJ4OvGux1NBFP5aVwzLTWWmNMH+Bda+3nxpjbfB1MRER8w1pYuhS++AK+/tq5YlitGtSpk0KDBiFHCsKcU862MmVyvx01KioGUOEoIoXTgZQDTsH4p3OFcUDTATx7ybM0q9SMqKgor+OJeC4vhWOiMeZJ4BbgEmNMIBDk21giIpLf9u51riyOGgUrV0JwMPTrB4MHw6WXwty5q+natavXMUVEClTOgjExPZHrm15/pGAUkaPyUjgOBG4C7rTW7jbG1ASG+zaWiIjkh4wMmDrVKRZ/+gkyM6F9e/joI7jhBggN9TqhiIg3DqQc4K35b/HOn++QmJ7IgCYDeK7LcyoYRU4iL6Oq7gbezLG+DecZRxER8VMrVzrF4ldfQWys8xziQw/B7bdD06ZepxMR8Y4KRpGzk5dRVTsC7wGNgeJAIJBkrS3n42wiInIGDhxwnln84gtYsgSCguCaa5xbUXv2hGJ5ucdERKSIikuJ460FTsGYkJbAgCbOM4zNKzf3OppIoZCXrxHvAzcAE4C2wCCgvi9DiYhI3v3xB7zwQhPmz4f0dGjVCt55B266CSpW9DqdiIi34lLiGBk9kskLJpOQlkD/Jv157pLnVDCKnKE8/f7ZWrvRGBNorc0CRhlj5vk4l4iInIK1MG0avPIK/P47lC0bxr33OlcXW7XyOp2IiPeS0pN4e8HbDJ83XAWjSD7IS+F4yBhTHFhujHkd2AWU9m0sERHJTWYmjB8Pr77qPMdYo4ZzdbF+/fn06nWJ1/FERDyXlpnGJ0s+4eW5L7M3eS99G/XlmtLXcMfVd3gdTaRQC8jDPre6+90PJAM1gOt8GUpERI6VkuKMhNqgAdx8s1NAjh4NmzbBv/4FJUtmex1RRMRTWdlZjF4+mobvN+TBnx+kaXhT5t85n0kDJ1EnpI7X8UQKvbxccdwHpFtrU4EX3fc4Bvs2loiIABw86BSMb7/tvIexQwd46y1n0JuAvPzqT0SkiLPWMnn9ZJ6e9TRrYtfQpkobPr3mUy6rcxnGGK/jiRQZefnaMRMolWO9JPBrXj/AGBNojFlmjPnRXY80xvxpjNlgjBnn3gaLMSbYXd/obq+d4xhPuu3rjTFX5Gjv6bZtNMY8kddMIiL+bvdueOIJqFULnnoKLrgAZs+G+fOhTx8VjSIiALOiZ3Hh5xfSb1w/srKzmDBgAovuWkSPuj1UNIrks7x89ShhrU06vOIulzrF/sd7EFibY/014C1rbX0gDrjTbb8TiLPW1gPecvfDGNMEZ1TXpkBP4EO3GA0EPgB6AU2AG919RUQKrU2b4N57oXZtGD4cevWCpUvh55+ha1fQ9yAREVi8czGX/+9yLv3yUnYk7uCzaz5j1X2r6N+kvwpGER/JS+GYbIxpfXjFGNMGSMnLwY0x1YGrgM/cdQN0B751dxkN9HWX+7jruNsvdffvA4y11qZZa6OBjUB7d9pord1srU0Hxrr7iogUOhs3hnDjjc4zjKNGwW23wfr1MHasc7VRRERg3b519B/fn3aftmPprqW8cfkbbHhgA3e2vpNiAXpZrYgvGWvtqXcwph1OUbbTbaoCDLTWLjntwY35FngFKAM8AtwOLHCvKmKMqQFMs9Y2M8asAnpaa2PcbZuADsALbp+v3PbPgWnuR/S01v7Dbb8V6GCtvT+XHHcDdwOEh4e3GT9+/Omin1RSUhIhISGe9VeG/OmvDP6ToSicw7kcY9u2UnzySR3mzatIyZKZ9O69kwEDYqhQIb1APj8/j1EUMhSFc1CG/OmvDPnTP78yJBdLZvTW0UzfPZ3gwGCur349A6oPoHSxvA307/Wfg7/8OSqD9/39JUO3bt2WWGvbnlEna+1pJyAIaAY0B4Ly2Odq4EN3uSvwIxCOc5Xw8D41gJXu8mqgeo5tm4AKOLej3pKj/XOcUV0HAJ/laL8VeO90uRo0aGDPxezZsz3trwz5018Z/CdDUTiHsznG3r3WDhlibWCgtWXLWnvHHZvtgQMF9/m+OEZRyFAUzkEZ8qe/MuRP/3M9RmxyrO3/aX8bPDTYFh9a3D407SG7N2lvgWbwh/7K4D8ZisI5WGstsNjmoabLOeXpmr61NgNYdUYVKXQGehtjrgRKAGWBt4FQY0wxa20mUJ2jVzJj3EIyxhhTDCgHHMjRfljOPidrFxHxS2lp8O67MGwYJCfDPffACy/A6tVbCQuL9DqeiIhfSM1M5d0/3+XluS+TlJbEba1u4/kuz1MrtJbX0UTOWz4bl89a+6S1trq1tjbO4DazrLU3A7OB/u5utwGT3eUp7jru9lluNTwFuMEddTUSqA8sBBYB9d1RWou7nzHFV+cjInIurIXx46FxY3jsMbj4Yli5Ej74AMLDvU4nIuIfrLV8s/IbGr3fiMd/fZyLa17MZ20/Y2SfkSoaRTx20sLRGNPZnef3OxsfB/7PGLMR51bUz932z4EKbvv/AU8AWGtXA+OBNcDPwBBrbZZ7xfJ+YDrOqK3j3X1FRPzKggXQuTMMHAghIfDLL/Djj04RKSIijt+3/U7Hzzty03c3EVoilF9v/ZUfb/qRyNK6G0PEH5zqVtV3gTbAfKD1KfY7LWttFBDlLm/GGRH1+H1ScZ5bzK3/y8DLubRPBaaeSzYREV/ZsgWefNIZGTUiAj77DG6/HQIDvU4mIuI/NuzfwBMzn+C7td9RrUw1vujzBbe0uIXAAP2wFPEnpyocM4wxo4Bqxph3j99orf2X72KJiBRe8fHwyivw9tsQEADPPuvcnnqOA6CJiBQp+w/tZ+icoXyw6AOCA4MZ2m0o/3fh/1Eq6ExeFy4iBeVUhePVwGU471087as3RETOd5mZzlXF556D2FgYNAhefhmqV/c6mYiI/0jLTOP9he8zbO4wEtIS+McF/+DFbi8SERLhdTQROYWTFo7W2n3AWGPMWmvtigLMJCJSqFgLCxaUZ8gQWLMGunSBN96ANm28TiYi4j+stUxYM4Enfn2C6IPR9KrXi+E9htO0UlOvo4lIHuTldRz7jTGTcF6vYYHfgQettTE+TSYiUggsXAjPPAMzZrSgfn2YNAn69AFjvE4mIuI/5m2fx79/+TcLYhbQonILfrnlF3rU7eF1LBE5A3l5HcconNdcVAWqAT+4bSIi563Fi+Hqq6FDB1i6FIYM2cCqVdC3r4pGEZHDNh3YxAurX6DzyM5sPbiVkb1HsvTupSoaRQqhvBSOlay1o6y1me70BaC3jonIeWnJEujdG9q1g/nz4T//geho6N9/B8WLe51ORMQ/pGelM2zOMJp+2JQ/D/zJi11fZMMDGxh8wWCNlipSSOXlVtVYY8wtwDfu+o3Aft9FEhHxP8uWwQsvwJQpEBYGw4bBAw9A2bJeJxMR8S/zts/jrh/uYk3sGgY2HUj/Mv3p36W/17FE5Bzl5YrjHcD1wG5gF9DfbRMRKfKWL4d+/aB1a5gzB156ybnC+PTTKhpFRHKKT43nvp/uo/PIziSlJ/HjjT8ytv9YKgZX9DqaiOSD015xtNZuA3oXQBYREb/x11/OFcZJk6BcOXjxRXjwQWdZRESOstby3drveGDaA+xJ3sPDHR/mpW4vEVJcL68VKUrycquqiMh5Y+VKp0icONG5ovj88/DQQxAa6nUyERH/sz1+O/dPu58p66dwQcQF/HDjD7SpqncRiRRFKhxFRIBVq5zbUCdMgDJl4Nln4eGHnecZRUTkWFnZWXy46EOemvUUWdlZDO8xnIc6PkSxAH21FCmq9H+3iJzXNmyAF19swm+/QUiI807Ghx+G8uW9TiYi4p/+2vMXd/1wFwt3LOSKulfw0VUfERkW6XUsEfGx0w6OY4x5JsdysG/jiIgUjMxMGD4cWrSAP/8sz5NPOoPeDB2qolFEJDcpGSk88esTtP6kNdFx0Xx97ddMu3maikaR88RJrzgaYx4D5uKMojrMbZ4PtC6AXCIiPrNqFdxxByxaBH37wi23LOS66zp5HUtExG/9uvlX7v3xXjbFbeKOVncw/PLhlC+p37KJnE9OdcVxPTAAqGOMmWuMGQFUMMY0LJhoIiL5KyPDuaLYurVzdXHcOPjuO6hQId3raCIifulg+kEGTRpEj//1IMAEMGvQLD7v87mKRpHz0KmecYwDngK6ulNj4ArgCWNMQ2utfj0vIoXG0qXOVcYVK+DGG+GddyA83OtUIiL+KT0rnRFLRvD0oqc5lH2IZy5+hqcveZoSxUp4HU1EPHKqwrEn8DxQF3gTWAEkW2sHF0QwEZH8kJrqjJb6+utQqRJ8/z306eN1KhER/5SVncXXK7/muajn2HJwCy3LteSrm76iWaVmXkcTEY+dtHC01j4FYIxZAXwFXACEG2N+B+KstdcUTEQRkbMzf75zlXHdOmf+3//q9RoiIrmx1vLD3z/w9KynWbV3FRdEXMDHN39M8e3FVTSKCJCHUVWB6dbaRdbaEUCMtfYiQFcdRcRvJSc7r9To3BkOHYLp0+Hzz1U0iojk5rctv9F5ZGf6jO1DWmYa4/qPY/Hdi7mi3hUYY7yOJyJ+4rTvcbTWPpZj9Xa3bZ+vAomInIvZs+Ef/4DNm+G+++DVV6FMGa9TiYj4n6W7lvLUzKeYvmk6VctUZcTVI7i91e0EBQZ5HU1E/NBpC8ecrLUrfBVERORcJCTA44/Dxx9DvXoQFQVdunidSkTE/2zYv4FnZz/LuNXjCCsRxvAewxnSbgglg0p6HU1E/FheblU9K8aYEsaYhcaYFcaY1caYF932SGPMn8aYDcaYccaY4m57sLu+0d1eO8exnnTb1xtjrsjR3tNt22iMecJX5yIi/u3PP8vTrBmMGAH//rczcqqKRhGRY+1I2ME9P9xD4w8aO88zXvw0mx/czCOdHlHRKCKndUZXHM9QGtDdWptkjAkCfjfGTAP+D3jLWjvWGPMxcCfwkTuPs9bWM8bcALwGDDTGNAFuAJoCVYFfjTEN3M/4AOgBxACLjDFTrLVrfHhOIuJH9uyBxx6DL79sQePG8Mcf0LGj16lERPzL/kP7ee2P13hv4XtkZWfxz7b/5OlLniYiJMLraCJSiPiscLTWWiDJXQ1yJwt0B25y20cDL+AUjn3cZYBvgfeN80R2H2CstTYNiDbGbATau/tttNZuBjDGjHX3VeEoUsRlZMB778GLL0JKCtxyy1Y++6wWwcFeJxMR8R9J6Ul8tfUrJiyYQGJaIre0uIUXu75IZFik19FEpBDy5RVHjDGBwBKgHs7VwU3AQWttprtLDFDNXa4GbAew1mYaY+KBCm77ghyHzdln+3HtHXxwGiLiR375BR580HnFRq9e8PbbsHNnNMHBtbyOJiLiF3Yl7uKDRR/w0eKPOJBygN4NezOs2zCaV27udTQRKcSMc2HQxx9iTCgwCXgOGGWtree21wCmWmubG2NWA1dYa2PcbZtwriy+BMy31n7ltn8OTMV5PvMKa+0/3PZbgfbW2gdy+fy7gbsBwsPD24wfP/6szyUpKYmQkBDP+itD/vRXBv/JkNf+O3eW4MMP6/HHHxWpVu0QQ4Zs5MILDxRoBl8ew+v+ypA//ZXBfzIUhXM402NsTtrMhJgJzNw7k0ybSecKnelTsQ9tI9oWyOf76hhFIUNROAdlyJ/+/pKhW7duS6y1Z/bDwVpbIBPwPPAosA8o5rZdiPOeSIDpwIXucjF3PwM8CTyZ4zjT3X5H+rrtx+x3sqlBgwb2XMyePdvT/sqQP/2VwX8ynK5/UpK1Tz9tbXCwtaVLW/vqq9amphZshoI4htf9lSF/+iuD/2QoCueQl2NkZ2fbnzf8bHt82cPyArbUy6XskJ+G2L/3/Z0vGc6XP0d/768M/pOhKJyDtdYCi+0Z1nM+u1XVGBMOZFhrDxpjSgKX4Qx4MxvoD4wFbgMmu12muOvz3e2zrLXWGDMF+NoY8ybO4Dj1gYVuUVnfGBMJ7MAZQOfws5MiUshZC+PGwSOPwI4dcOutzjsZq1b1OpmIiPfSMtMYs3IMb85/k9Wxq4kIieDl7i9zb9t7KV+yvNfxRKQI8uUzjlWA0e5zjgHAeGvtj8aYNcBYY8wwYBnwubv/58D/3MFvDuAUglhrVxtjxuMMepMJDLHWZgEYY+7HuQIZCIy01q724fmISAFZvhz+9S+YOxfatIHx46FTJ69TiYh4b9+hfXy8+GPeX/g+e5L30LxSc77o8wU3NLuB4GIaIUxEfMeXo6r+BVyQS/tmjo6KmrM9FRhwkmO9DLycS/tUnOcdRaQI2LcPnn3WeR9j+fLw6acweDAEBnqdTETEW3/v/5u35r/F6BWjSclMoWe9nvz7wn9zaeSlOIPQi4j4lk9HVRURyYvMTPjkE6doTEhwrjY+/zyEhnqdTETEO9Zalh9czpvfvMmPf/9IUGAQt7a4lYc7PkzTSk29jici5xkVjiLiqeXLQ/nXv2DlSrj0Unj3XWjSxOtUIiLeybbZTFk/hZfnvszinYupULICz1zyDEPaDaFySGWv44nIeUqFo4h4IiEBHn4YRo5sRe3a8N130Lcv6I4rETlfZdtsJq2dxEtzXuKvPX9RN6wuD9d/mGEDhlEqqJTX8UTkPBfgdQAROf/MnQstW8IXX8DNN29lzRro109Fo4icn7JtNuNXj6flxy3pP6E/qZmpfNn3S9bdv47eVXuraBQRv6ArjiJSYNLSnGcXX38d6tSB33+HtLRoSpas5XU0EZECl5WdxYQ1Exg6ZyhrYtfQqGIjvur3FTc0u4HAAI0KJiL+RYWjiBSIVavglltgxQq4+2544w0ICYGoKK+TiYgUrKzsLMauGsuwucNYt28dTcKb8M113zCgyQAVjCLit1Q4iohPZWfDW2/BU085o6T+8ANcfbXXqURECl5mdibfrPyGYXOH8ff+v2lWqRnj+o+jf5P+BBg9PSQi/k2Fo4j4zNatcPvtzlXFvn2d9zOGh3udSkSkYGVmZzLmrzEMmzuMjQc20qJyC74d8C39GvdTwSgihYYKRxHJd9bC//4HDzzgLI8aBbfdpsFvROT8kpmdychlI3l57stsjttMq4hWfHf9d/Rp1EcFo4gUOiocRSRf7dsH994LEyfCxRfD6NEQGel1KhGRgrM9fjvjV4/njUVvsCt1F62rtGbyDZO5psE1GP0GTUQKKRWOIpJvpk2DO+6A/fvhtdfg3/+GQI3zICLngV2Ju5iwZgLjVo9j3vZ5ADQp04QR/UZwVf2rVDCKSKGnwlFEzllyMjzyCHz8MTRrBj//7LynUUSkKNubvJeJayYybvU45mydg8XSvFJzhnUbxsBmA4n5K4auDbp6HVNEJF+ocBSRc7JmTRnuvhs2bnSKx6FDoUQJr1OJiPjGgZQDfLf2O8atHses6Flk22waVWzEc12eY2DTgTQOb3xk3xhiPEwqIpK/VDiKyFnJzIRhw2Do0NZUrw6zZkHXrl6nEhHJf/Gp8UxeP5lxq8fxy6ZfyMzOpG5YXZ7o/AQDmw2keaXmuhVVRIo8FY4icsZ27ICbboI5c6BHjz1MmBBBuXJepxIRyT+JaYnM3DuTt8e+zbSN00jPSqdmuZo83PFhBjYdSOsqrVUsish5RYWjiJyRadNg0CBISXFGTK1Zcx3lykV4HUtE5LRSMlLYk7yHPUl7jpnvTtp9wnpCWgIAVctU5b629zGw2UA6VOugYlFEzlsqHEUkTzIy4Jln4PXXoUULGDcOGjWCqCivk4mIHGtN7Bre2/geH8R+4BSFbkF4uBg8XmiJUCJCIqhcujKtIlpRuXRlIkIiKL2/NA/0eUDvXBQRQYWjiOTB1q1www2wYAHccw+89RaULOl1KhGRY1lr+WL5FwyZOoTs7Gwi0yKpXLoyF1S54EgxWLl0ZSqHHF2uVLoSwcWCcz1eVFSUikYREZcKRxE5pe+/h8GDISsLxo6FgQO9TiQicqLEtETum3ofX/31Fd1qd2NIxBCuu+I6r2OJiBQZ+jWaiOQqLQ0eegg+ickaAAAgAElEQVT69YO6dWHZMhWNIuKfVuxeQdtP2/L1yq95seuLzLh1BhWCK3gdS0SkSNEVRxE5wcaNTpG4dKlTPL76KgTnfieXiIhnrLV8suQTHvr5IcqXLM/MQTPpWrur17FERIokFY4icoxx4+CuuyAw0LlNtU8frxOJiJwoPjWeu364iwlrJnBF3Sv4st+XVCpdyetYIiJFls9uVTXG1DDGzDbGrDXGrDbGPOi2lzfGzDDGbHDnYW67Mca8a4zZaIz5yxjTOsexbnP332CMuS1HextjzEq3z7tGY2SLnLWUFGfgmxtugGbNYPlyFY0i4p8W71xM6xGt+W7td7x66atMvXmqikYRER/z5TOOmcC/rbWNgY7AEGNME+AJYKa1tj4w010H6AXUd6e7gY/AKTSB54EOQHvg+cPFprvP3Tn69fTh+YgUWevWQYcOMGIEPP44/PYb1KrldSoRkWNZa3lnwTt0+rwTGVkZzBk8h8cvelwjn4qIFACf/aS11u6y1i51lxOBtUA1oA8w2t1tNNDXXe4DfGkdC4BQY0wV4ApghrX2gLU2DpgB9HS3lbXWzrfWWuDLHMcSkTyaPr0ybdrArl0wbZrzPGNQkNepRESOdSDlAH3H9eWh6Q/Rs15Plt2zjE41OnkdS0TkvGGcmsvHH2JMbWAO0AzYZq0NzbEtzlobZoz5EXjVWvu72z4TeBzoCpSw1g5z258FUoAod//L3PaLgcettVfn8vl341yZJDw8vM348ePP+lySkpIICQnxrL8y5E9/ZYDExGJ88EE9pk+PoGXLgzzzzBoqVkwv0Az50V8Z8qe/MuRPf2XwTYbV8asZunYo+9P3c0+de7iu2nWc7ukUfzuHwpqhKJyDP2QoCuegDPnT318ydOvWbYm1tu0ZdbLW+nQCQoAlwLXu+sHjtse585+Ai3K0zwTaAI8Cz+Rofxb4N9AO+DVH+8XAD6fL06BBA3suZs+e7Wl/Zcif/udzhowMaz/80NoKFaw1xtpBg6JtRkbBZsjP/sqQP/2VIX/6K0P+ZsjKzrKv/f6aDXwx0Ea+HWkXxiwssM/Pj2MUhQxF4Rz8IUNROAdlyJ/+/pIBWGzPsK7z6UMBxpggYCIwxlr7ndu8x73NFHe+122PAWrk6F4d2Hma9uq5tIvISfz6K1xwAdx3HzRv7rybcfDgLRTT+Moi4mcOph/k6q+v5vFfH6df434su2cZ7aq18zqWiMh5y5ejqhrgc2CttfbNHJumAIdHRr0NmJyjfZA7umpHIN5auwuYDlxujAlzB8W5HJjubks0xnR0P2tQjmOJSA4bNzojpPboAcnJMHEizJoFLVt6nUxE5Kj41HiW717OmL/GcNeSu5gVPYsPr/yQ8f3HU65EOa/jiYic13x5naEzcCuw0hiz3G17CngVGG+MuRPYBgxwt00FrgQ2AoeAwQDW2gPGmKHAIne/l6y1B9zlfwJfACWBae4kIq74eBg2DN55B4KD4ZVX4KGHoEQJr5OJyPkoJSOFLQe3EH0w2pnHRRN90J3ioolLjTuyb/WS1ZkxeAatIlp5mFhERA7zWeFonUFuTvbk+qW57G+BISc51khgZC7ti3EG3BGRHLKyYORIeOYZiI2F22+Hl1+GKlW8TiYiRV1mdiZ/bPuDn3b9xK+zfj1SFEYfjGZ30u5j9g0ODKZ2aG0iwyLpUK0DkaGRRIZFEhkayf51+1U0ioj4ET3ZJFLE/Pabc1Vx+XLo3BmmToU2bbxOJSJF3drYtYxaPoovV3zJnuQ9AARuCKRGuRpEhkZyZb0rjxSFh+eVQyqf9B2MUX9HFWB6ERE5HRWOIkVEdDQ8+qjz/GLNmjB2LFx/PZxmxHoRkbOWkJbAuFXjGLV8FPNj5lMsoBhX1b+KQS0HkbYljQFXDKBYgL5qiIgUBfppLlLIJSY6zy6++SYEBsJLL8Ejj0DJkl4nE5GiKNtmM2frHEYtH8WE1RNIyUyhSXgT/tvjv9zS4hYqh1QGIGpPlIpGEZEiRD/RRQqp7Gz4+ecIbrwRdu+GW25xCsjq1U/fV0TkTG2P387oFaMZtXwUm+M2Uza4LINaDmJwq8G0r9Yeo9sbRESKNBWOIoVQQgIMGAC//NKIDh1g0iTo2NHrVCJS1KRmpjJ53WRGLh/JjE0zsFi6R3bnxa4vcm3jaykVVMrriCIiUkBUOIoUMjt2wFVXwerV8PDDf/Pf/zYgwGdvZBWR8421lr8T/+bbqd/y9cqviUuNo2a5mjx7ybPc3up2IsMivY4oIiIeUOEoUoisXg29ekFcHPz0ExQvvpOAgAZexxKRQs5ay8q9K5m4ZiLfrv2WNbFrCA4M5trG13LHBXfQPbL7SUc/FRGR84MKR5FCIioK+vaFUqVg7lxo1cppExE5G9Zalu5ayrdrvmXi2olsOLCBABPAJbUu4fLQy3mu33OElQzzOqaIiPgJFY4ihcA338Dtt0PdujBtGtSq5XUiESmMsm02C3csPFIsbjm4hUATSPfI7jzS6RH6NupLpdKViIqKUtEoIiLHUOEo4sesheHD4fHH4ZJL4PvvIUzf5UTkDGRlZzFv+7wjxeKOxB0EBQTRo24PnrvkOXo37E2FUhW8jikiIn5OhaOIn8rKggcfhA8+gIEDYfRoCA72OpWIFAZZNotZ0bP4ds23fLf2O/Yk7yE4MJie9XryapNXubrB1YSWCPU6poiIFCIqHEX80KFDcNNNMHkyPPIIvPYaGjlVRE4pPSudWdGzmLhmIhNWTSB+TjylgkpxZf0r6d+4P1fWv5IywWW8jikiIoWUCkcRPxMbC717w59/wrvvwgMPeJ1IRPxVSkYKv2z6hYlrJzJl/RTi0+IpU7wM7cLaMaTrEHrW66l3LYqISL5Q4SjiRzZtgp49ISYGJk6Efv28TiQi/iYpPYmpG6Yyce1Efvr7J5IzkgkrEUa/xv24rvF1XFbnMhb8voCujbt6HVVERIoQFY4ifmLhQrj6asjOhlmz4MILvU4kIv7iYOpBflj/AxPXTmT6pumkZqZSqXQlbm5+M/2b9Kdr7a4EBQZ5HVNERIowFY4ifmDKFLjhBoiIgJ9/hgYNvE4kIl7bd2gf36/7nolrJzJz80wysjOoVqYad7W+i+saX8dFNS8iMCDQ65giInKeUOEo4rGPPoL774fWreHHH6FyZa8TiYhXdibu5Psd3zP0y6FEbYki22YTGRrJgx0e5Lom19G+WnsCjEbKEhGRgqfCUcQj2dnw6aeRfP21c4vq2LFQurTXqUSkoG3Yv4FJ6yYxad0kFsQsAKBhhYY80fkJrmtyHRdEXIAxxuOUIiJyvlPhKOKBdevg+edh/Pha3HMPvP8+FNP/jSLnBWstK/as4Lu13zFp3SRW7V0FQOsqrRnabSjVEqtx+5W3q1gUERG/oq+qIgUkORnGj4fPP4c//nAKxX/8YzMffVQHfT8UKdqysrOYt33ekSuLWw5uIcAEcFHNi3jrirfo26gvtUNrAxAVFaWiUURE/I4KRxEfshYWLYLPPnNuRU1MdAa+ef11GDQI1q7dhjF1vI4pIj6QlpnGrOhZTFo3icnrJ7M3eS/FA4tzWZ3LePrip+ndsDeVSlfyOqaIiEie+KxwNMaMBK4G9lprm7lt5YFxQG1gC3C9tTbOOL9afQe4EjgE3G6tXer2uQ14xj3sMGvtaLe9DfAFUBKYCjxorbW+Oh+RM7F/P3z1lVMwrloFJUvC9dfDP/4BnTtz5Arj2rXe5hSR/JWUnsRvsb8xYuIIftrwEwlpCYQUD+HK+ldybaNr6VW/F2WDy3odU0RE5Iz58orjF8D7wJc52p4AZlprXzXGPOGuPw70Auq7UwfgI6CDW2g+D7QFLLDEGDPFWhvn7nM3sACncOwJTPPh+YicUnY2zJzp3Io6aRKkp0O7dvDxx86rNsqV8zqhiOS3rOwslu5ayozNM/hl0y/M2z6PjOwMKpaqyIAmA+jXqB+X1rmUEsVKeB1VRETknPiscLTWzjHG1D6uuQ/Q1V0eDUThFI59gC/dK4YLjDGhxpgq7r4zrLUHAIwxM4CexpgooKy1dr7b/iXQFxWO4oHt22HUKGfasgXCwuDee+HOO6FFC6/TiUh+23JwCzM2zWDG5hnMjJ7JgZQDALSKaMXDHR+mSnIV7u99P8UC9DSIiIgUHQX9r1pla+0uAGvtLmPM4Yc7qgHbc+wX47adqj0ml3aRApGaCr/9VpHXXoPp051nGS+7DF55Bfr2hRK6uCBSZCSkJTA7eja/bPqFGZtnsOHABgCqlalG74a9ubzO5Vxa59IjzytGRUWpaBQRkSLH+PKxQPeK4485nnE8aK0NzbE9zlobZoz5CXjFWvu72z4TeAzoDgRba4e57c/iPAM5x93/Mrf9YuAxa+01J8lxN85trYSHh7cZP378WZ9TUlISISEhnvVXhvzpfzbHSEgoxp9/VuD33yuyaFEYKSnFqFgxjV69dtGr126qVEn1eYb87u8PGYrCOfhDhqJwDv6QISkpiZKlS7I2YS1L4pawOG4xaxLWkE02JQJK0Cq0FW3C2tA2rC21StXKdfRTr89BGfKnvzLkT39lyJ/+yuA/GYrCOQB069ZtibW27Rl1stb6bMIZBGdVjvX1QBV3uQqw3l3+BLjx+P2AG4FPcrR/4rZVAdblaD9mv1NNDRo0sOdi9uzZnvZXhvzpn9djREdb+/bb1nbrZm1goLVgbZUq1t5zj7WvvbbcZmb6PoMv+/tDhqJwDv6QoSicg1cZsrKz7LJdy+zb89+2F713kS37SlnLC1jzgrHtRrSzT/36lI2KjrJpmWk+y5Cf/ZUhf/orQ/70V4b86a8M/pOhKJyDtdYCi+0Z1nYFfS/NFOA24FV3PjlH+/3GmLE4g+PEW+dW1unAf4wxYe5+lwNPWmsPGGMSjTEdgT+BQcB7BXkiUjRZC8uWwfffw+TJ8NdfTnuTJvD449CnD7RtCwEBEBUVR2Cgt3lF5MxlZmeyfPdyftvyG79t/Y252+ZyMPUgABElIhjYdCA96vSge2R3KpSq4HFaERER/+DL13F8gzO4TUVjTAzO6KivAuONMXcC24AB7u5TcV7FsRHnVtTBAG6BOBRY5O73knUHygH+ydHXcUxDA+PIWUpPh99+cwrFKVOcwW4CApzXZvz3v06xWK+e1ylF5GxlZGWwZNeSI4Xi79t+JzE9EYB65etxXePr6FKrC11qd2Hzss107drV28AiIiJ+yJejqt54kk2X5rKvBYac5DgjgZG5tC8Gmp1LRjl/JSTArFnhjBgBU6dCfLzzrsXLL4eXXoKrroLwcK9TisjZSMtMY9HORUcKxXnb55GckQxA44qNubn5zXSp3YVLal1C1TJVj+m7mc1eRBYREfF7GvZNzhvZ2RAVBSNHwsSJkJralPBwuO4656riZZdBqVJepxSRs7Fh/wYmrp3IuOXjWPfHOlIzncGqmldqzuBWg48UiodHPhUREZEzo8JRirytW+GLL5xpyxYoVw4GD4bGjZdx330X6DlFkUJqbexavl3zLd+u/Za/9jgPJNcLqce9be6lS+0uXFzzYj2jKCIikk9UOEqRlJLiDHAzciTMnOm0XXop/Oc/znsWS5aEqKh4FY0ihYi1lpV7V/Ltmm+ZuHYia2LXYDB0rtmZt694m2sbX8umZZv0jKKIiIgPqHCUIsNaWLLEKRa/+QYOHoTateGFF+C226BWLa8TisiZstaydNdSJq6dyLdrvmXDgQ0EmAC61OrCfW3vo1/jfsc8p7iJTR6mFRERKbpUOEqhFxsLY8Y4BePKlVCihPPc4h13QNeuzgipIlJ4WGtZuGPhkdtQtxzcQqAJpHtkdx7p9Ah9G/XVs4oiIiIFTIWjFEpZWYaffnKKxR9+gIwMaN8ePvoIbrgBQkO9TigiZyIlI4WFOxby/sb3GbRsENsTthMUEESPuj147pLn6N2wt55XFBER8ZAKR/FLWVmwdy/ExMCOHSfOly+/kLg455UZDzzgDHbTTC9nESkUsrKzWLtvLQt3LDwyrdy7kszsTIJMEL0a9OLl7i9zTcNrCC2h3wKJiIj4AxWOUuCysmDXrhLMnXvywnDnTme/nIoVg2rVoHp1aN06jiFDKnPVVVC8uDfnISKnZ60lJiHmaJG4cyGLdy4mKT0JgHLB5WhXrR2PdXqM9tXaExQTxJWXXelxahERETmeCkcpMGlpMGoUvPoqbN3a8ZhtpUs7BWG1atCt29HlnPPw8KPPK0ZFraVr18oenIWInMrB1IMs2rHoSJG4cMdCdiftBqB4YHFaRbTi9pa3075ae9pXa0/9CvUJMEcfRI7aHeVRchERETkVFY7icykp8Nln8NprztXEDh3guuvWc8UVDY8UhWXLgjFeJxWR3FhrSUpPIvZQLLHJsexN3ntkOfbQ0fXVO1az/bftR/o1rNCQHnV6HCkSW1ZuSXCxYA/PRERERM6WCkfxmeRk+OQTGD4cdu+Giy92rjhedhn89tsuunZt6HVEkfNats1mV+IuNsVtYnPcZuZtm8cP039g76G9R4rCw4ViWlZarscoFVSK8FLhhJcOp1apWtx74b20r9aetlXb6vlEERGRIkSFo+S7xET44AN44w3Ytw+6d4exY6FLF6+TiZx/ktOTiT4Yzea4zWyO28ymA5vYfNBZjo6LPqEgLBVTikqlKxFeKpyIkAhaVG7hFIZucXh4W3hpp6108dJH+kZFRdH14q4FfIYiIiJSEFQ4Sr45eBDeew/efhsOHICePeHZZ6FTJ6+TiRRdh68aroxfydblW50C0S0MN8dtPvJ84WFlipehbvm6NA1vyjUNrqFOWB3qhNUhMjSSTcs30fPSnh6diYiIiPgzFY5yzg4ccIrFd9+F+Hi45hp45hnnvYoicu7iUuKOXDWMjosm+mD0kfWtB7cevWq4HAJMADXK1qBOWB2uqn8VdcPqHikO64TVoXzJ8piTPFC8I3BHAZ6ViIiIFCYqHOWsxcbCm2/C++9DUhJce61TMF5wgdfJRAqXlIwUth3axrQN05zi0C0Mo+Oc4jA+Lf6Y/cuXLE9kaCQtKregb8O+RIZFkrAtgWu7XkvNcjUpHqh31IiIiEj+UuEoZ2zXLvjww7r89JMzYur118PTT0Pz5l4nE/E/WdlZ7E7azbb4bWxP2M62+G3HLG+P307soVhn50XOrESxEkSGRhIZFkmnGp2IDI10bicNiyQyNJJyJcqd8DlRSVHUK1+vAM9MRMSPWetM2dlgLSY93fnSkp19VlPJbdtg7dojxztmnlvbcdtCly078bi59T9+Ocd65dWrYevWU3/eKbLV2LgRFiw44c/myDwPbXW3bYPJk3PfnoflRrt3w6efnlXfw8stDhyA0NCjbcfvc5qpdUIChIQ46zn/ruRxvV1yMpQsefrPOkWmTunpEBR09PjHz3NryzG/KDMTAgOPtufcJ6/LZ0GFo+QqK8v52fT33860fv3R5W3bICCgOjffDE89BY0aeZ1WxBvWWg6mHmR7wnbm75/P2kVrTygQdyTuIDM785h+ZYqXoWa5mtQsV5N2VdtRo2wNDu06xFWdriIyNJLKIZWPebehiPgxayEjw3lZ8XFT6Y0bnfdNZWY6/7BmZeW+fIrtVdaudQqWrCzni+jx89zacszrbt3qfNE/y0Kh8e7dMGJE3gqsnJlyTBccPOh8UT9++6nWcyx3Sks7+iU5r0XXcc51fL4O59i/1Tn2B2h8jv3r5mUnY5yXZhtz7LI7r5Kd7RQ8x2/P43K5tDQoVeqs+h5eDjx0KG8ZTjJlBARAhQpH2w6fdx7Xk/fupXTlyqf+nNPk2LdrF1WrVj32+MfPT7Ftd0wM1WvUOLb9TJeHD8/L34hjqHA8j1kLe/ceLQhzFombNkF6+tF9y5WDhg3hkkuceWTkQm6++Vx/jIr4r5xFYUxCDNvj3XnCsfNDGYeOdloFxQKKUb1sdWqWq8nFtS6mRtkaR4rEw8u5XjGMiqJTDY0kJYWUtU7Bk57uTBkZBMXFOf/InOXxgmNjnX+UDh1yppSUo8t5WG++axeEhZ0682kytIyNda4spKbmWhgemU5yrHZnd/bHOOMXVwUGOl9a3XkVa6FYsRMKgNyKgtzayqalQenSznpepsOfHxDgfK4xZKWnQ/nyJ27P43rszp1Uq1nzaK6cGY9fzm2bMWzeupU69erl/TyOO9aatWtp0rz5iX9Gx/8ZnmTb8hUraNW69enzn+xcjGHBwoV07NTp5J93mhxz5s7lkq5dT/7fPg8v1P49KoquXbuexd9kx5/n2B9g2TkeY+U59l8TFUWlczyHv6OiqHoOx9gYFUX1c8ygwlFOkJ4OMTGwZcvRaf78xjz2mPPvcXyOR6eKF4d69ZzC8JprnHmDBs4UHn7sz5OoqJQCPhOR/JOZncmepD3sStrF7qTdzNo5i5mzZhKTeGyBeExRiDPwTJWQKtQoV4MWlVtwVf2rqF62OtXLVmffpn307daXyqUrExgQ6NGZSZGSne38EE9LO3GeW1uOecRffzlXqTIyjhRyxyyfqi09nRZ79zrFQs5tOYrCY9YPtx2n8zme/oVnsnPx4s5VjFKlnEKvVCmC0tNPXxye5ouyycx0jhcWBsHBJ59KlMi1fdXff9OsVSunGAoMdAqpvC6783l//kmniy46tqg6fn54OZfz8Ycv+n+d4zE2REVR7RwzbIuKos45HGNvVBRNzqH/QWOc376fg9QdOyAy8qz7Z5cs6fx9FjlLKhwLufR059bRrVuPLQ4PTzt3HnvHRkAAhIeXo3lzuOWWo4VhgwZQq5bz745IYXUo4xC7k3azK3EXu5J2HZ27BeLh9djkWCzHfqEM2Hi0KGxeuTlX1r+S6mWrU6NsDWdergYRIREUC8j9x2ZUbBRVy1QtiNOUM5GZeWKhdbL1tDTCly1zfnAeLqpON2VmntDWZMcOZ5jpnNvysuyuX5ya6rRnZp7+/E7ipE8QBAQ4t3gVL5773F0OTElxirDSpZ1th6fD+56qzT3O3xs20KBBg7M+h/XR0TS84IIjheDxheEx67n847U0Hwqe5ed4jH1RUXCOGdI3boTKlc/pGCIi+UGFo5+y1nnNxZ49x067d8PixY155pmjhWHOX6gGBED16lC7NnTv7swPT7VqOdvmzVtwzv+YivhSZnYmB1MPEpcSR1xqHAdSDuS6fHg9em808QviSUhLOOFYgSaQiJAIqpRxisL21dpTJaQKVcpUOTLfsnIL115+7UmLQskHWVmQnOwMwXyKqcbq1TBnTu63A+Z2u+BxbZ2Skpzflh0uDHN51ulUmuZ1x8NF1uGpWLEjyyEZGc79/TnaCApyCpyyZU/Y//jlnbt3U6NePeeqVfHix87z0la8OPOXLOHCLl1OLArz+NvBc70VDGBnVBQNzuEYu6KiaKh/q0RE/Ia+JRWgjAyIjw9i9ercC8Kc63v35nrnD8WKQcWKZWnUCC677NjCsHZtqFbt6CBNIgUtKzuLxPREEtMS8zZPT2RTzCaKbS3mFIJuQZhbAZhTqaBShJUIo3zJ8oSVDKNO6Tq0qNPiSCEYERJxZLliqYqnHWjm0IZD3haN2dkEpKdDYuLJr2zlvLUwl6nSihXO7QenuJJ1uvXGu3fDJ584mXK7xe/4tuPWm+7e7dyyl1tRmJK329uPDN4QEHDs7X/H3wpYooRztSks7Jhtsfv3Uy0y8sTCKi/rwcEsXL6c9p07n7IwPNktgYctPMeia1NUFDXOsWBKi4mBiIhzOoaIiEhOhb5wNMb0BN4BAoHPrLWv5rWvtc4vwXN+hzrdfPnyciQlOd/vEhKcec4pt7bD7WlpkNtTH0FBUKmS8298RAS0bOnclXJ4iog4uhwWBnPm/KkrhnJWMrMzSctMIzUzlbSsNNIy04hOjqZkTEmSM5JJTk8+Mj+UceiEtuSM5BPaYuNjyVycSWJaIimZeSsOAk0gZYLLUKZ4GQIyA6he0rkltEV4M8KKlyMsuBxhxctRvng5woqVISyoDGHFylC+WAihgaUJptgxow8uXrCAtuVbOevxmbA/EzJ3Q2bM0Vv+Dk+H/4fOMdVYv94ZovwU+5xyW0YGLWJjnVEDz6Zws5Zze/IFmuRlp8O3KZ7kSleZww9FH5ZbcXR82/+3d+5RlhX1vf/8TndPT8+Lp0QUFEeBYDRORhQVGQFDlqLXRy5EXdFcISyjCT5wmXt1kRXQrCQqJho1agwqXMX4IuGSSAJeEnAiyvAcGBh5OvJwHB5RYKC7Z06fX/6oOj17es6uU7W7dXpOfz+rzzr79a39q72/Z++qXbWrK/NjExPhgrVs2Y7vks/SpXx33TrWnHBCiK0Bs30X6olHHgl994UQQgixE3t0xdHMhoC/BU4A7gOuMbOL3f3WOs2ddy5jbGw2r4/0/u/2y5bB8uU7PitWhK6hM5dt2XIHRx996C6VwYyBrMQehrsz5VNMdaaY6rSZmmoz1d7G1NR2ptrbmZpq8+DDd7HxthHGJ7cyPrGV8W2PMz75ePje9jgT28YZ3/4E49vj99QE4+0JxtvjjE9N8uDPH+KcdYuZ7GxnsrOdCd/GpLeZ9O3xu80E25lkiknadKgZKOLa+ny0HJZ2hlnaGWLJ1BBLO0MsnWqxtN1i/3aLQ8fb7GeLWb5tL5Zv35vl22D5NmP5pLN8EpZPeJie6ITp8Q6LJ9vYVBvaD9Jpt2lN3TOr/y10ZGNlYJchyrsDU3QrV70+1XVDQwxNTIT3wbrdEWd2U+wzf/e997Ly8MN3bemqvHdWu25khHU33LBrS9nM7pCtdMvrbFvKrp2D7o2dsbHGlUYhhBBC/OLY0+/OLwTudPe7Aczsa8BrgdqK494r7uF3Xve+MAjZELSs8l03GvP0eue/fvYABz31AEZGnJFFHspyw2DWLfTGITcqhWCvTG6G+j8AABVESURBVLe238u2R5/KPY8499wWtsd3bB+2jcu6hXzfMe/ubN68mR+tPz/urRM398rmnR2ReNymEseWLVv44TWfwTs+nWb3fzdNa7xTmd913cMPP8z1l+9NJ1aMOu50vEPHp+J39eN02Hl+6xOP84//NEZMNXziMfQYq1ucrgxj0p0fnxjnvIsWT8fl1fi6eaosn7nOcSa3b+fjXx+ibR2mcNq24zNzvm3OVHe6xY75S6EDTJkz1YIpi58WeO7DgA15m5nD2HZY3Iax9o7pxT+F0SkYbcOK9o7p6vfidmVZxxjttFjcaTHqLUa3wQpGQoWwM8xSH97pe9SGsaHKiH8zRv772WOPsc/+++88GuDoMCzpPULgzO9777+fp69cuevIgqlRB2fM37xxI89dvbq+kten4rf2qqs45vjjd6TZ4EnObN8Jm+2If088/DA8M+u/dAkhhBBCFGM+i6f8uxszOwl4hbufFuffAhzl7qfP2O5twNsAOJDn8we/7EgXJq1OaK1qEb/dpufNwQDDdkxXrGg127DT8rCuuj1Y+PMZ6yrbEqdbDiO0aLkx7MaQG8O0GHJjiO6yFsMYLcL3kLcYosUQBlPOSGuYIWthGEPWokVY38JoWXe6Nb2uZeFj3e06xtJFSxm1RYwOLWKRjTI6NMro8GIWtUZZNLyYRcNjjA6PMTS0CIaH8cpn68QES5Yvx1stPA7H3p32OF1d1qvFaevWrSxbtqzxed7desUwN3rFMDd6xTB/YhiEPMyHGAYhD/MhhkHIg2KYG/18ieG44467zt2LOm3t6S2OvZoFdqkJu/vngc8DPPNpT/FvH/fpxjvccMutPPc5z4l7N6zSMjE9bRYqKT3WrV9/E6tWrdr5H61O/+PVkCWbXtd7mxtuuJHVq1djccAPi/+81brbQVhXicNihcHMWHfNNRx11Iti/KEy0U0DwGKLy/Q62/HPYbvbXfW9q1hzzJrpitCQDU1Pt6y103HpxRWzbJ2ZrX6QYnjRPIhhEI7jnh7DIORhPsQwCHlQDHOjVwxzo1cMc6NXDPMnhkHIQ1P29IrjfcDBlfmDgJ+kBMNjy/nVNb/deIc/7ezL4ccc21h/7/gYK1/YXA/w4wfbHPLslzTW7/Wjh3jywUfMKoZlw8tYMbpiVmkIIYQQQggh9gzSIyXMf64BDjWzZ5jZIuCNwMW7OSYhhBBCCCGEGCj26BZHd2+b2enApYR/x/FFd79lN4clhBBCCCGEEAPFHl1xBHD3S4BLdnccQgghhBBCCDGo7OldVYUQQgghhBBC/IJRxVEIIYQQQgghRBJVHIUQQgghhBBCJFHFUQghhBBCCCFEElUchRBCCCGEEEIkUcVRCCGEEEIIIUQSVRyFEEIIIYQQQiQxd9/dMfxSMbPHgNtmkcT+wEO7Ua8Y5kavGOZPDIOQh/kQwyDkYT7EMAh5UAxzo1cMc6NXDHOjVwzzJ4ZByAPA4e6+vEjh7gvqA1y7J+sVw+DkQTEMTh7mQwyDkIf5EMMg5EExDE4e5kMMg5CH+RDDIORBMQxOHpqmoa6qQgghhBBCCCGSqOIohBBCCCGEECLJQqw4fn4P1yuGudErhvkTwyDkYT7EMAh5mA8xDEIeFMPc6BXD3OgVw9zoFcP8iWEQ8tAojQU3OI4QQgghhBBCiDIWYoujEEIIIYQQQogCFkzF0cy+aGYPmNmGhvqDzew/zGyjmd1iZu8u1C82s3Vmtj7qP9gwjiEzu8HM/qWhfpOZ3WxmN5rZtQ30e5vZt8zsh/FYvLhQf3jcd/fzqJm9pzCNM+Ix3GBm/2Bmiwv1747aW3L33cs/ZravmX3HzO6I3/sU6k+OMXTM7MiGMZwTz8VNZvZPZrZ3of7PovZGM7vMzJ5SGkNl3fvMzM1s/8IYzjaz+yueOLFJDGb2TjO7LR7TjxbG8PXK/jeZ2Y2F+lVm9oPu78rMXliaBzN7npl9P/4+/9nMViT0Pa9HuZ5M6LM9mUgjy5MJfZYn6/SV9Tl+rIshy5OpGAr8WBdDlicT+ixPJvQlfux5fzOzZ5jZ1dGPXzezRYX6083szn7nsU8aF8TzsMHC726kUP+FuOwmC/e+ZaUxVNZ/ysy2NsjDeWb2o4ofVhXqzcz+3Mxuj+f5XQ1iWFvZ/0/M7KJC/cvN7Pqo/08ze1aDGI6PaWwws/PNbLgujbj9TuWlXD8m9Nl+TKSR5ceEPtuPvfSV5Ukv9okhy48JfbYfE2lk+TGhz/Zjjb7Ui7uUva2gDJlIo+Se3UufXYacZrZDue4pH2ANsBrY0FB/ILA6Ti8HbgeeXaA3YFmcHgGuBl7UII73Al8F/qVhPjYB+8/iOJ4PnBanFwF7zyKtIeCnwNMLNE8FfgSMxflvAG8t0D8H2AAsAYaB/w8c2sQ/wEeB98fp9wMfKdQfARwOXAEc2TCG3wKG4/RHGsSwojL9LuBzpTHE5QcDlwI/TvmrJoazgfcVnMNeaRwXz+VonD+gNA+V9X8F/Gnh/i8DXhmnTwSuaJCHa4CXxelTgT9L6Htej3I9mdBnezKRRpYnE/osT9bpC/1YF0OWJxP6Ej/2vbekPJmIIcuTCX2JH3ve3wjX5zfG5Z8D3lGo/w3gEDLuW4k0TozrDPiHBjFU/fjXxN9XSRpx/kjgy8DWBnk4Dzgpw491+lOA/wu0MvzYt6wCXAj8XmEMtwNHxOV/CJxXGMNLgHuBw+LyDwG/3+d47FReyvVjQp/tx0QaWX5M6LP92Euf68U+MWT5MaHP9mMqHzl+TMSQ7ceZekKjW6kXd/EMBWXIRBol9+xe+uwyZPezYFoc3f27wH/NQr/Z3a+P048BGwmVmFy9u3v36c5I/BS9YGpmBwGvAs4t0c0VFp44rwG+AODu29z957NI8uXAXe7+40LdMDAWn/AsAX5SoD0C+IG7P+HubeBK4PX9RDX+eS2hIk38fl2J3t03uvttuYHXpHFZzAfAD4CDCvWPVmaX0seTid/Rx4H/PQt9NjVpvAP4sLtPxm0eaBKDmRnwO4QbeonegW6LzF708WRNGocD343T3wH+Z0Jfdz3K8mSdvsSTiTSyPJnQZ3myzzU514+zva7X6Uv8mIyhnycT+ixPJvQlfqy7vx0PfCsuT/mxp97db3D3TXX7zUzjkrjOgXXU+7FO/yhMn4cxEp6qS8PMhoBzCJ4szkNKk6l/B/Ahd+/E7VJ+TMZgZssJ57VnC09Cn32NrEljCph099vj8qQnZ5aX4vnL8mMvfYwr24+JNLL8mNBn+7GXPteLqTRKqNFn+7FfDP38mNBn+7GHfj8KvJgguwxZR8k9u0afXYbssmAqjnOJmR1CePJ0daFuyEJ3oweA77h7kR74BOHH3inUVXHgMjO7zszeVqhdCTwIfCk22Z9rZktnEcsbSRTQe+Hu9wMfA+4BNgOPuPtlBUlsANaY2X5mtoTw9O/gkhgq/Iq7b45xbQYOaJjOXHEq8K+lothl5F7gd4E/baB/DXC/u68v1VY4PXaV+GK/7ho1HAYcY6Eb0pVm9oKGcRwDbHH3Owp17wHOicfxY8AHGux7A/CaOH0ymb6ccT0q9mTT61lmGlmenKkv9WRV39SPPfJQ5MkZ+kZ+rDmO2Z6coS/25Ax9kR9n3t+Au4CfVwol95GolM/B/TGZhoUugW8B/q1Ub2ZfIvSO+VXgUw1iOB24uPvbbJiHP49+/LiZjRbqnwm8wUKX5X81s0MbxgDhQevlMx7w5OhPAy4xs/sI5+HDJTEQKlkjle54J5H25Mzy0n4U+LGHvgm1aeT4sU5f4Mde+mwvpmIg0481+iI/JmKADD/W6Ev8OFP/EGVehN5l79L79WzK7zn6rPu1Ko6FWOhPfiHwnj5G3QV3n3L3VYQa/QvN7DkF+3018IC7X1cU8K4c7e6rgVcCf2Rmawq0w4TudZ91998AHic0rxdj4d2C1wDfLNTtQ3hK8wzgKcBSM3tzrt7dNxKa479DuGCvB9pJ0R6AmZ1JyMcFpVp3P9PdD47a0wv3uwQ4kwYVzgqfJdxIVhEeBvxVgzSGgX0IXaL+GPhGfCJbypsofJgReQdwRjyOZxBb5Qs5lfCbvI7QZXBbP8FsrkdzoU+lkevJXvoST1b1cX/FfuwRQ5Ene+iL/Zg4F1me7KEv8mQPfZEfZ97fCL07dtksV19yf8xM4zPAd919bane3U8h3G82Am8ojGENoeKdrHD2ieEDhErCC4B9gf9TqB8FJtz9SODvgS82iKFLXz/W6M8ATnT3g4AvEbpZZqcB/BrhYfPHzWwd8Bg19+6a8lKv319PP85FeSsjjaQfU/ocP/bSW3hfPNuLiRiy/JjQZ/sx4zgm/ZjQZ/mxlz62Fmd5scJsyt5zlUatvqgM6Zl9lAfhQ+ib3ugdx6gfIbw38945iOUsyt7r+kvCE7JNhCdNTwBfmWUMZxfG8GRgU2X+GODbDff9WuCyBrqTgS9U5n8P+MwsjsFfAH/YxD/AbcCBcfpA4LYm/iPzHce6NID/BXwfWNJEX1n39JzfRzUN4LmEJ8Kb4qdNaA1+csMYsn6jPc7FvwHHVubvAp5UeByHgS3AQQ32/whM/3sjAx6d5bk4DFjXR7/L9ajEk730pZ6sSyPXk6kYcjw5U9/Qj/1iSHqy5jyU+rHuOGZ5siaGbE9mHIO+fpyx/VmECvND7Hh/5sXApQX691XmN1H4bn41jTh9EfGdqiYxxGUvo2B8gZjGWYR7dteTHeDOWcRwbG4MXT3wQ+CQihceaXgc9wMeBhY38MJdlWVPA26d5bn4LeAbNdv3Ki9dkOvHGv1XKuv7+jGVRo4f+8XQz481+p+VeDEzhlo/1ulL/NjnOPb1Y43+27l+zDwGtV6sSfNswu+yqAzZK43K/BVkliNn6ikoQ7q7Ko4FWiO8zPuJhvonEQeSIfRLXwu8umFatT/UPrqlwPLK9FXAKwrTWAscHqfPBs5pmIevAac00B0F3EJ4t9EI/cLfWZjGAfH7afECtk8T/xDeE6i+2PzRJv4r+cH3iOEVwK0kCqV99IdWpt8JfKs0jRnrNtH/hjozhgMr02cAX2uQj7cT3pmAUMi9l1hozs1DPJZXNjyOG4kVBcK7u9c1SKPryxbhWnNqQtvzepTryTp9iScTMWR5MqHP8mS/POT4MRFDlicT+mw/pvKR48lEDFmeTOhL/Njz/kboUVIdjKTnQ7o6fe557BPDaYR73VgD/f8AnlU5Th8DPlYaw4xtUoPj1OXhwEoMnyC8P1ui/3D3/BHKD9c0yUP09fkNz8ND7BhM5PeBCxuk0fXkKHA5cHwqlkp+uwOiZPmxTl/ix0QMWX7spY/nP9uPqTz082KfPGT5MaHP9mMqHzl+rDmOwyV+rMlDthepKXtTUIasS6Oy/goS9+xEDEVlSPcFVHEkNGVvBrYTnh4kR0DqoX8poVvDTcCN8XNigf7XgRuifgOJURsz0up5EcjQrSR0zVxPqHyd2SCNVcC1MR8XkVnpmpHGEsJTor0a5v+DhArfBsLIYKOF+rXxh7IeeHlT/xCedl0O3BG/9y3Uvz5OTxJaFZJP42vSuJNQKO16snZU1Br9hfE43gT8M2Fwksa/I/oX1HvF8GXg5hjDxVQK7QVpLCI8ydwAXE/6It4zD4SR4t7e0AsvBa6LnroaeH6DNN5NGOntdsKNNVXx7Xk9yvVkQp/tyUQaWZ5M6LM8Wacv9GNdDFmeTOhL/FibjxxPJmLI8mRCX+LHnvc3wj1nXfTEN6m5Vif074p+bBMGrzi3QQxtQotvN291o9PuoidUmr8XvbCB0Gq1ojSGGdukKo51efj3SgxfIY44WqDfm9DKcjOhZeF5TfJAKJwmHzYnYnh93P/6mM7KBmmcQ3ggchuhS3XyWh01x7KjsJ/lx4Q+24+JNLL82Etf6sde+8/1Yp88ZPkxoc/2YyofOX5MxJDtxxp9thepKXtTVoasSyPrnp3QZ5chu59uNxYhhBBCCCGEEKInGhxHCCGEEEIIIUQSVRyFEEIIIYQQQiRRxVEIIYQQQgghRBJVHIUQQgghhBBCJFHFUQghhBBCCCFEElUchRBCDDxmNmVmN5rZBjP7ppktKdSfa2bPLtj+rWb26R7LX2Nm7y/cdzf2W8xsvZm918x0/xZCCPFLRf+OQwghxMBjZlvdfVmcvgC4zt3/OlM75O5Thft7K+EfMp9eHOyuaVVjPwD4KvA9dz9rtmkLIYQQueiJpRBCiIXGWuBZAGb2ZjNbF1v0/s7MhuLyrWb2ITO7GnixmV1hZkfGdW8ys5tj6+VHuoma2SlmdruZXQkc3WvH1ZZIMzvPzD5pZleZ2d1mdlK/wN39AeBtwOkWOMTM1prZ9fHzkpj2l83stZX9XhBbO3+tkt+bzOzQhsdQCCHEAkMVRyGEEAsGMxsGXgncbGZHAG8Ajnb3VcAU8Ltx06XABnc/yt3/s6J/CvAR4HhgFfACM3udmR0IfJBQYTwByO3WeiDwUuDVwIdzBO5+N+H+fQDwAHCCu6+Oeflk3Oxc4JQY817AS4BLgLcDfxPzeyRwX2acQgghFjjDuzsAIYQQ4pfAmJndGKfXAl8gtNw9H7jGzADGCBUxCJXIC3uk8wLgCnd/EKa7va6J66rLvw4clhHXRe7eAW41s18pyI/F7xHg02bWrfgeBuDuV5rZ38aurb8NXOjubTP7PnCmmR0E/KO731GwTyGEEAsYVRyFEEIsBMZjK9s0FmqL57v7B3psP1HzXqP1WNalyaABk5lp79jIbCWhkvgAcBawBXgeoRVyorLplwktqG8ETgVw96/G7revAi41s9Pc/d8bxC2EEGKBoa6qQgghFiqXAyfFVjnMbF8ze3ofzdXAy8xs//g+5JuAK+PyY81sPzMbAU7+RQRsZk8CPgd82sPodnsBm2Or5VuAocrm5wHvAXD3W6J+JXC3u38SuBj49V9EnEIIIQYPtTgKIYRYkLj7rWb2J8Bl8d9bbAf+CPhxQrPZzD4A/AehhfASd/9/AGZ2NvB9YDNwPTtX4mZDt5vtCNAmtCR2R4T9DHChmZ0cY3q8EusWM9sIXFRJ6w3Am81sO/BT4ENzFKMQQogBR/+OQwghhBhA4v+qvBlY7e6P7O54hBBC7Nmoq6oQQggxYJjZbwI/BD6lSqMQQoi5QC2OQgghhBBCCCGSqMVRCCGEEEIIIUQSVRyFEEIIIYQQQiRRxVEIIYQQQgghRBJVHIUQQgghhBBCJFHFUQghhBBCCCFEElUchRBCCCGEEEIk+W80Lsm6y1rnIQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Everyday 1556.6 people got infected in from 22nd Jan 2020 to 13th March 2020.\n",
      "The rate at which the population got infected from 22nd Jan 2020 to 13th March 2020 was 0.00563.\n",
      "3.93% population suffered death from 22nd Jan 2020 to 13th March 2020.\n",
      "79.31% population recovered from 22nd Jan 2020 to 13th March 2020.\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(china_df)+1)\n",
    "tick_locations_china = []\n",
    "for x in x_axis:\n",
    "    tick_locations_china.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 cases in China \")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "confirmed_cases_china, = plt.plot(x_axis, china_df.loc[:,'#Cumulative Confirmed Cases'], color=\"blue\", label=\"Cumulative Confirmed Cases\")\n",
    "death_cases_china, = plt.plot(x_axis, china_df.loc[:,'#Cumulative Death Cases'], color=\"red\", label=\"Cumulative Deaths\")\n",
    "recovered_cases_china, = plt.plot(x_axis, china_df.loc[:,'#Cumulative Recovered Cases'], color=\"green\", label=\"Cumulative Recovered Cases\")\n",
    "\n",
    "plt.legend(handles=[confirmed_cases_china, recovered_cases_china, death_cases_china], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_china)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "print(f\"Everyday {speed_infection_china} people got infected in from 22nd Jan 2020 to 13th March 2020.\")\n",
    "print(f\"The rate at which the population got infected from 22nd Jan 2020 to 13th March 2020 was {infection_rate_china}.\")\n",
    "print(f\"{percentage_death_china}% population suffered death from 22nd Jan 2020 to 13th March 2020.\")\n",
    "print(f\"{percentage_recovered_china}% population recovered from 22nd Jan 2020 to 13th March 2020.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Everyday 41.9 people got infected from 22nd Jan 2020 to 13th March 2020.\n",
      "The rate at which the population got infected from 22nd Jan 2020 to 13th March 2020 was 0.00066.\n",
      "2.16% population suffered death from 22nd Jan 2020 to 13th March 2020.\n",
      "0.55% population recovered from 22nd Jan 2020 to 13th March 2020.\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(US_df)+1)\n",
    "tick_locations_US = []\n",
    "for x in x_axis:\n",
    "    tick_locations_US.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 cases in US \")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "confirmed_cases_US, = plt.plot(x_axis, US_df.loc[:,'#Cumulative Confirmed Cases'], color=\"blue\", label=\"Cumulative Confirmed Cases\")\n",
    "death_cases_US, = plt.plot(x_axis, US_df.loc[:,'#Cumulative Death Cases'], color=\"red\", label=\"Cumulative Deaths\")\n",
    "recovered_cases_US, = plt.plot(x_axis, US_df.loc[:,'#Cumulative Recovered Cases'], color=\"green\", label=\"Cumulative Recovered Cases\")\n",
    "\n",
    "plt.legend(handles=[confirmed_cases_US, recovered_cases_US, death_cases_US], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_US)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "print(f\"Everyday {speed_infection_US} people got infected from 22nd Jan 2020 to 13th March 2020.\")\n",
    "print(f\"The rate at which the population got infected from 22nd Jan 2020 to 13th March 2020 was {infection_rate_US}.\")\n",
    "print(f\"{percentage_death_US}% population suffered death from 22nd Jan 2020 to 13th March 2020.\")\n",
    "print(f\"{percentage_recovered_US}% population recovered from 22nd Jan 2020 to 13th March 2020.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Everyday 3.7 people got infected from 22nd Jan 2020 to 13th March 2020.\n",
      "The rate at which the population got infected from 22nd Jan 2020 to 13th March 2020 was 0.00051.\n",
      "0.52% population suffered death from 22nd Jan 2020 to 13th March 2020.\n",
      "4.15% population recovered from 22nd Jan 2020 to 13th March 2020.\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(canada_df)+1)\n",
    "tick_locations_canada = []\n",
    "for x in x_axis:\n",
    "    tick_locations_canada.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 cases in Canada \")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "confirmed_cases_canada, = plt.plot(x_axis, canada_df.loc[:,'#Cumulative Confirmed Cases'], color=\"blue\", label=\"Cumulative Confirmed Cases\")\n",
    "death_cases_canada, = plt.plot(x_axis, canada_df.loc[:,'#Cumulative Death Cases'], color=\"red\", label=\"Cumulative Deaths\")\n",
    "recovered_cases_canada, = plt.plot(x_axis, canada_df.loc[:,'#Cumulative Recovered Cases'], color=\"green\", label=\"Cumulative Recovered Cases\")\n",
    "\n",
    "plt.legend(handles=[confirmed_cases_canada, recovered_cases_canada, death_cases_canada], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_canada)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "print(f\"Everyday {speed_infection_canada} people got infected from 22nd Jan 2020 to 13th March 2020.\")\n",
    "print(f\"The rate at which the population got infected from 22nd Jan 2020 to 13th March 2020 was {infection_rate_canada}.\")\n",
    "print(f\"{percentage_death_canada}% population suffered death from 22nd Jan 2020 to 13th March 2020.\")\n",
    "print(f\"{percentage_recovered_canada}% population recovered from 22nd Jan 2020 to 13th March 2020.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "153.0 people per day got infected throughout 52 days.\n",
      "The rate at which the population got infected from 22nd Jan 2020 to 13th March 2020 was 0.01556.\n",
      "0.83% population suffered death from 22nd Jan 2020 to 13th March 2020.\n",
      "6.39% population recovered from 22nd Jan 2020 to 13th March 2020.\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(southKorea_df)+1)\n",
    "tick_locations_southKorea = []\n",
    "for x in x_axis:\n",
    "    tick_locations_southKorea.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 cases in South Korea \")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "confirmed_cases_southKorea, = plt.plot(x_axis, southKorea_df.loc[:,'#Cumulative Confirmed Cases'], color=\"blue\", label=\"Cumulative Confirmed Cases\")\n",
    "death_cases_southKorea, = plt.plot(x_axis, southKorea_df.loc[:,'#Cumulative Death Cases'], color=\"red\", label=\"Cumulative Deaths\")\n",
    "recovered_cases_southKorea, = plt.plot(x_axis, southKorea_df.loc[:,'#Cumulative Recovered Cases'], color=\"green\", label=\"Cumulative Recovered Cases\")\n",
    "\n",
    "plt.legend(handles=[confirmed_cases_southKorea, recovered_cases_southKorea, death_cases_southKorea], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_southKorea)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "print(f\"{round(speed_infection_southKorea,0)} people per day got infected throughout {total_days_southKorea} days.\")\n",
    "print(f\"The rate at which the population got infected from 22nd Jan 2020 to 13th March 2020 was {infection_rate_southKorea}.\")\n",
    "print(f\"{percentage_death_southKorea}% population suffered death from 22nd Jan 2020 to 13th March 2020.\")\n",
    "print(f\"{percentage_recovered_southKorea}% population recovered from 22nd Jan 2020 to 13th March 2020.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Everyday 3.8 people got infected in from 22nd Jan 2020 to 13th March 2020.\n",
      "The rate at which the population got infected from 22nd Jan 2020 to 13th March 2020 was 0.00343.\n",
      "0.0% population suffered death from 22nd Jan 2020 to 13th March 2020.\n",
      "48.5% population recovered from 22nd Jan 2020 to 13th March 2020.\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(singapore_df)+1)\n",
    "tick_locations_singapore = []\n",
    "for x in x_axis:\n",
    "    tick_locations_singapore.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 cases in Singapore \")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "confirmed_cases_singapore, = plt.plot(x_axis, singapore_df.loc[:,'#Cumulative Confirmed Cases'], color=\"blue\", label=\"Cumulative Confirmed Cases\")\n",
    "death_cases_singapore, = plt.plot(x_axis, singapore_df.loc[:,'#Cumulative Death Cases'], color=\"red\", label=\"Cumulative Deaths\")\n",
    "recovered_cases_singapore, = plt.plot(x_axis, singapore_df.loc[:,'#Cumulative Recovered Cases'], color=\"green\", label=\"Cumulative Recovered Cases\")\n",
    "\n",
    "plt.legend(handles=[confirmed_cases_singapore, recovered_cases_singapore, death_cases_singapore], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_singapore)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "print(f\"Everyday {speed_infection_singapore} people got infected in from 22nd Jan 2020 to 13th March 2020.\")\n",
    "print(f\"The rate at which the population got infected from 22nd Jan 2020 to 13th March 2020 was {infection_rate_singapore}.\")\n",
    "print(f\"{percentage_death_singapore}% population suffered death from 22nd Jan 2020 to 13th March 2020.\")\n",
    "print(f\"{percentage_recovered_singapore}% population recovered from 22nd Jan 2020 to 13th March 2020.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Everyday 153.4 people got infected from first confirmed case (19th Feb 2020) to 13th March 2020.\n",
      "The rate at which the population got infected from first confirmed case (19th Feb 2020) to 13th March 2020 was 0.00962.\n",
      "0.83% population suffered death from first confirmed case (19th Feb 2020) to 13th March 2020.\n",
      "6.39% population recovered from first confirmed case (19th Feb 2020) to 13th March 2020.\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(iran_df)+1)\n",
    "tick_locations_iran = []\n",
    "for x in x_axis:\n",
    "    tick_locations_iran.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 cases in Iran \")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "confirmed_cases_iran, = plt.plot(x_axis, iran_df.loc[:,'#Cumulative Confirmed Cases'], color=\"blue\", label=\"Cumulative Confirmed Cases\")\n",
    "death_cases_iran, = plt.plot(x_axis, iran_df.loc[:,'#Cumulative Death Cases'], color=\"red\", label=\"Cumulative Deaths\")\n",
    "recovered_cases_iran, = plt.plot(x_axis, iran_df.loc[:,'#Cumulative Recovered Cases'], color=\"green\", label=\"Cumulative Recovered Cases\")\n",
    "\n",
    "plt.legend(handles=[confirmed_cases_iran, recovered_cases_iran, death_cases_iran], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_iran)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "print(f\"Everyday {speed_infection_iran} people got infected from first confirmed case (19th Feb 2020) to 13th March 2020.\")\n",
    "print(f\"The rate at which the population got infected from first confirmed case (19th Feb 2020) to 13th March 2020 was {infection_rate_iran}.\")\n",
    "print(f\"{percentage_death_iran}% population suffered death from first confirmed case (19th Feb 2020) to 13th March 2020.\")\n",
    "print(f\"{percentage_recovered_iran}% population recovered from first confirmed case (19th Feb 2020) to 13th March 2020.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Everyday 339.6 people got infected from first confirmed case (31st Jan 2020) to 13th March 2020.\n",
      "The rate at which the population got infected from first confirmed case (31st Jan 2020) to 13th March 2020 was 0.02917.\n",
      "7.17% population suffered death from first confirmed case (31st Jan 2020) to 13th March 2020.\n",
      "8.15% population recovered from first confirmed case (31st Jan 2020) to 13th March 2020.\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(italy_df)+1)\n",
    "tick_locations_italy = []\n",
    "for x in x_axis:\n",
    "    tick_locations_italy.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 cases in Italy \")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "confirmed_cases_italy, = plt.plot(x_axis, italy_df.loc[:,'#Cumulative Confirmed Cases'], color=\"blue\", label=\"Cumulative Confirmed Cases\")\n",
    "death_cases_italy, = plt.plot(x_axis, italy_df.loc[:,'#Cumulative Death Cases'], color=\"red\", label=\"Cumulative Deaths\")\n",
    "recovered_cases_italy, = plt.plot(x_axis, italy_df.loc[:,'#Cumulative Recovered Cases'], color=\"green\", label=\"Cumulative Recovered Cases\")\n",
    "\n",
    "plt.legend(handles=[confirmed_cases_iran, recovered_cases_iran, death_cases_iran], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_italy)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "print(f\"Everyday {speed_infection_italy} people got infected from first confirmed case (31st Jan 2020) to 13th March 2020.\")\n",
    "print(f\"The rate at which the population got infected from first confirmed case (31st Jan 2020) to 13th March 2020 was {infection_rate_italy}.\")\n",
    "print(f\"{percentage_death_italy}% population suffered death from first confirmed case (31st Jan 2020) to 13th March 2020.\")\n",
    "print(f\"{percentage_recovered_italy}% population recovered from first confirmed case (31st Jan 2020) to 13th March 2020.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Everyday 13.5 people got infected from first confirmed case (31st Jan 2020) to 13th March 2020.\n",
      "The rate at which the population got infected from first confirmed case (31st Jan 2020) to 13th March 2020 was 0.00056.\n",
      "2.71% population suffered death from first confirmed case (31st Jan 2020) to 13th March 2020.\n",
      "16.83% population recovered from first confirmed case (31st Jan 2020) to 13th March 2020.\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(japan_df)+1)\n",
    "tick_locations_japan = []\n",
    "for x in x_axis:\n",
    "    tick_locations_japan.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 cases in Japan \")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "confirmed_cases_japan, = plt.plot(x_axis, japan_df.loc[:,'#Cumulative Confirmed Cases'], color=\"blue\", label=\"Cumulative Confirmed Cases\")\n",
    "death_cases_japan, = plt.plot(x_axis, japan_df.loc[:,'#Cumulative Death Cases'], color=\"red\", label=\"Cumulative Deaths\")\n",
    "recovered_cases_japan, = plt.plot(x_axis, japan_df.loc[:,'#Cumulative Recovered Cases'], color=\"green\", label=\"Cumulative Recovered Cases\")\n",
    "\n",
    "plt.legend(handles=[confirmed_cases_japan, recovered_cases_japan, death_cases_japan], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_japan)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "print(f\"Everyday {speed_infection_japan} people got infected from first confirmed case (31st Jan 2020) to 13th March 2020.\")\n",
    "print(f\"The rate at which the population got infected from first confirmed case (31st Jan 2020) to 13th March 2020 was {infection_rate_japan}.\")\n",
    "print(f\"{percentage_death_japan}% population suffered death from first confirmed case (31st Jan 2020) to 13th March 2020.\")\n",
    "print(f\"{percentage_recovered_japan}% population recovered from first confirmed case (31st Jan 2020) to 13th March 2020.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Merged (CONFIRMED)\n",
    "###\n",
    "###\n",
    "\n",
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(italy_df)+1)\n",
    "tick_locations_italy = []\n",
    "for x in x_axis:\n",
    "    tick_locations_italy.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 Confirmed Cases\")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "confirmed_cases_italy, = plt.plot(x_axis, italy_df.loc[:,'#Cumulative Confirmed Cases'], color=\"blue\", label=\"Cumulative Confirmed Cases in Italy\")\n",
    "confirmed_cases_iran, = plt.plot(x_axis, iran_df.loc[:,'#Cumulative Confirmed Cases'], color=\"green\", label=\"Cumulative Confirmed Cases in Iran\")\n",
    "confirmed_cases_singapore, = plt.plot(x_axis, singapore_df.loc[:,'#Cumulative Confirmed Cases'], color=\"red\", label=\"Cumulative Confirmed Cases in Singapore\")\n",
    "confirmed_cases_southKorea, = plt.plot(x_axis, southKorea_df.loc[:,'#Cumulative Confirmed Cases'], color=\"cyan\", label=\"Cumulative Confirmed Cases in South Korea\")\n",
    "confirmed_cases_canada, = plt.plot(x_axis, canada_df.loc[:,'#Cumulative Confirmed Cases'], color=\"magenta\", label=\"Cumulative Confirmed Cases in Canada\")\n",
    "confirmed_cases_US, = plt.plot(x_axis, US_df.loc[:,'#Cumulative Confirmed Cases'], color=\"orange\", label=\"Cumulative Confirmed Cases in United States\")\n",
    "confirmed_cases_china, = plt.plot(x_axis, china_df.loc[:,'#Cumulative Confirmed Cases'], color=\"black\", label=\"Cumulative Confirmed Cases in China\")\n",
    "confirmed_cases_japan, = plt.plot(x_axis, japan_df.loc[:,'#Cumulative Confirmed Cases'], color=\"yellow\", label=\"Cumulative Confirmed Cases in Japan\")\n",
    "\n",
    "plt.legend(handles=[confirmed_cases_italy, confirmed_cases_iran, confirmed_cases_singapore,confirmed_cases_southKorea,confirmed_cases_canada,confirmed_cases_US,confirmed_cases_china,confirmed_cases_japan], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_italy)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Merged (DEATHS)\n",
    "###\n",
    "###\n",
    "\n",
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(italy_df)+1)\n",
    "tick_locations_italy = []\n",
    "for x in x_axis:\n",
    "    tick_locations_italy.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 Mortal Cases\")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "death_cases_italy, = plt.plot(x_axis, italy_df.loc[:,'#Cumulative Death Cases'], color=\"blue\",linestyle='dashed', label=\"Cumulative Mortal Cases in Italy\")\n",
    "death_cases_iran, = plt.plot(x_axis, iran_df.loc[:,'#Cumulative Death Cases'], color=\"green\", linestyle='dashed',label=\"Cumulative Mortal Cases in Iran\")\n",
    "death_cases_singapore, = plt.plot(x_axis, singapore_df.loc[:,'#Cumulative Death Cases'], color=\"red\",linestyle='dashed', label=\"Cumulative Mortal Cases in Singapore\")\n",
    "death_cases_southKorea, = plt.plot(x_axis, southKorea_df.loc[:,'#Cumulative Death Cases'], color=\"cyan\",linestyle='dashed', label=\"Cumulative Mortal Cases in South Korea\")\n",
    "death_cases_canada, = plt.plot(x_axis, canada_df.loc[:,'#Cumulative Death Cases'], color=\"magenta\",linestyle='dashed', label=\"Cumulative Mortal Cases in Canada\")\n",
    "death_cases_US, = plt.plot(x_axis, US_df.loc[:,'#Cumulative Death Cases'], color=\"orange\",linestyle='dashed', label=\"Cumulative Mortal Cases in United States\")\n",
    "death_cases_china, = plt.plot(x_axis, china_df.loc[:,'#Cumulative Death Cases'], color=\"black\",linestyle='dashed', label=\"Cumulative Mortal Cases in China\")\n",
    "death_cases_japan, = plt.plot(x_axis, japan_df.loc[:,'#Cumulative Death Cases'], color=\"yellow\",linestyle='dashed', label=\"Cumulative Mortal Cases in Japan\")\n",
    "\n",
    "plt.legend(handles=[death_cases_italy, death_cases_iran, death_cases_singapore,death_cases_southKorea,death_cases_canada,death_cases_US,death_cases_china,death_cases_japan], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_italy)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Merged (DEATHS)\n",
    "###\n",
    "###\n",
    "\n",
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(italy_df)+1)\n",
    "tick_locations_italy = []\n",
    "for x in x_axis:\n",
    "    tick_locations_italy.append(x)\n",
    "    \n",
    "plt.title(\"Cumulative Covid-19 Recovered Cases \")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "recovered_cases_italy, = plt.plot(x_axis, italy_df.loc[:,'#Cumulative Recovered Cases'], color=\"blue\",linestyle='dashdot', label=\"Cumulative Recovered Cases in Italy\")\n",
    "recovered_cases_iran, = plt.plot(x_axis, iran_df.loc[:,'#Cumulative Recovered Cases'], color=\"green\",linestyle='dashdot', label=\"Cumulative Recovered Cases in Iran\")\n",
    "recovered_cases_singapore, = plt.plot(x_axis, singapore_df.loc[:,'#Cumulative Recovered Cases'], color=\"red\",linestyle='dashdot', label=\"Cumulative Recovered Cases in Singapore\")\n",
    "recovered_cases_southKorea, = plt.plot(x_axis, southKorea_df.loc[:,'#Cumulative Recovered Cases'], color=\"cyan\",linestyle='dashdot', label=\"Cumulative Recovered Cases in South Korea\")\n",
    "recovered_cases_canada, = plt.plot(x_axis, canada_df.loc[:,'#Cumulative Recovered Cases'], color=\"magenta\",linestyle='dashdot', label=\"Cumulative Recovered Cases in Canada\")\n",
    "recovered_cases_US, = plt.plot(x_axis, US_df.loc[:,'#Cumulative Recovered Cases'], color=\"orange\",linestyle='dashdot', label=\"Cumulative Recovered Cases in United States\")\n",
    "recovered_cases_china, = plt.plot(x_axis, china_df.loc[:,'#Cumulative Recovered Cases'], color=\"black\",linestyle='dashdot', label=\"Cumulative Recovered Cases in China\")\n",
    "recovered_cases_japan, = plt.plot(x_axis, japan_df.loc[:,'#Cumulative Recovered Cases'], color=\"yellow\", linestyle='dashdot', label=\"Cumulative Recovered Cases in Japan\")\n",
    "\n",
    "plt.legend(handles=[recovered_cases_italy, recovered_cases_iran, recovered_cases_singapore,recovered_cases_southKorea,recovered_cases_canada,recovered_cases_US,recovered_cases_china,recovered_cases_japan], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_italy)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "day_china = np.arange(1, len(china_df))\n",
    "day_US = np.arange(1, len(US_df))\n",
    "day_canada = np.arange(1, len(canada_df))\n",
    "day_southKorea = np.arange(1, len(southKorea_df))\n",
    "day_singapore = np.arange(1, len(singapore_df))\n",
    "day_iran = np.arange(1, len(iran_df))\n",
    "day_italy = np.arange(1, len(italy_df))\n",
    "day_japan = np.arange(1, len(japan_df))\n",
    "\n",
    "new_cases_perday_china = [0]\n",
    "new_cases_perday_US = [0]\n",
    "new_cases_perday_canada = [0]\n",
    "new_cases_perday_southKorea = [0]\n",
    "new_cases_perday_singapore = [0]\n",
    "new_cases_perday_iran = [0]\n",
    "new_cases_perday_italy = [0]\n",
    "new_cases_perday_japan = [0]\n",
    "\n",
    "diff_confirmed_cases_china = china_df.loc[0,\"#Cumulative Confirmed Cases\"]\n",
    "diff_confirmed_cases_canada = canada_df.loc[0,\"#Cumulative Confirmed Cases\"]\n",
    "diff_confirmed_cases_US = US_df.loc[0,\"#Cumulative Confirmed Cases\"]\n",
    "diff_confirmed_cases_singapore = singapore_df.loc[0,\"#Cumulative Confirmed Cases\"]\n",
    "diff_confirmed_cases_southKorea = southKorea_df.loc[0,\"#Cumulative Confirmed Cases\"]\n",
    "diff_confirmed_cases_italy = italy_df.loc[0,\"#Cumulative Confirmed Cases\"]\n",
    "diff_confirmed_cases_iran = iran_df.loc[0,\"#Cumulative Confirmed Cases\"]\n",
    "diff_confirmed_cases_japan = japan_df.loc[0,\"#Cumulative Confirmed Cases\"]\n",
    "\n",
    "for new_cases in day_china:\n",
    "    \n",
    "    new_cases_perday_china.append(diff_confirmed_cases_china)\n",
    "    diff_confirmed_cases_china = china_df.loc[new_cases,\"#Cumulative Confirmed Cases\"] - china_df.loc[new_cases-1,\"#Cumulative Confirmed Cases\"]\n",
    "for new_cases1 in day_canada:\n",
    "    \n",
    "    new_cases_perday_canada.append(diff_confirmed_cases_canada)\n",
    "    diff_confirmed_cases_canada = canada_df.loc[new_cases,\"#Cumulative Confirmed Cases\"] - canada_df.loc[new_cases-1,\"#Cumulative Confirmed Cases\"]\n",
    "for new_cases2 in day_US:\n",
    "    \n",
    "    new_cases_perday_US.append(diff_confirmed_cases_US)\n",
    "    diff_confirmed_cases_US = US_df.loc[new_cases2,\"#Cumulative Confirmed Cases\"] - US_df.loc[new_cases2-1,\"#Cumulative Confirmed Cases\"]\n",
    "\n",
    "for new_cases3 in day_singapore:\n",
    "    \n",
    "    new_cases_perday_singapore.append(diff_confirmed_cases_singapore)\n",
    "    diff_confirmed_cases_singapore = singapore_df.loc[new_cases3,\"#Cumulative Confirmed Cases\"] - singapore_df.loc[new_cases3-1,\"#Cumulative Confirmed Cases\"]\n",
    "\n",
    "for new_cases4 in day_southKorea:\n",
    "    \n",
    "    new_cases_perday_southKorea.append(diff_confirmed_cases_southKorea)\n",
    "    diff_confirmed_cases_southKorea = southKorea_df.loc[new_cases4,\"#Cumulative Confirmed Cases\"] - southKorea_df.loc[new_cases4-1,\"#Cumulative Confirmed Cases\"]\n",
    "\n",
    "for new_cases5 in day_italy:\n",
    "    \n",
    "    new_cases_perday_italy.append(diff_confirmed_cases_italy)\n",
    "    diff_confirmed_cases_italy = italy_df.loc[new_cases5,\"#Cumulative Confirmed Cases\"] - italy_df.loc[new_cases5-1,\"#Cumulative Confirmed Cases\"]\n",
    "\n",
    "for new_cases6 in day_iran:\n",
    "    \n",
    "    new_cases_perday_iran.append(diff_confirmed_cases_iran)\n",
    "    diff_confirmed_cases_iran = iran_df.loc[new_cases6,\"#Cumulative Confirmed Cases\"] - iran_df.loc[new_cases6-1,\"#Cumulative Confirmed Cases\"]\n",
    "    \n",
    "for new_cases7 in day_japan:\n",
    "    \n",
    "    new_cases_perday_japan.append(diff_confirmed_cases_japan)\n",
    "    diff_confirmed_cases_japan = japan_df.loc[new_cases7,\"#Cumulative Confirmed Cases\"] - japan_df.loc[new_cases7-1,\"#Cumulative Confirmed Cases\"]\n",
    "\n",
    "#len(new_cases_perday_china)\n",
    "\n",
    "china_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"China\",:].index.tolist(),\\\n",
    "                       \"New cases per day\":new_cases_perday_china,\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"China\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"China\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"China\",:].tolist()})\n",
    "US_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"US\",:].index.tolist(),\\\n",
    "                       \"New cases per day\":new_cases_perday_US,\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"US\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"US\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"US\",:].tolist()})\n",
    "canada_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Canada\",:].index.tolist(),\\\n",
    "                       \"New cases per day\":new_cases_perday_canada,\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Canada\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Canada\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Canada\",:].tolist()})\n",
    "southKorea_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Korea, South\",:].index.tolist(),\\\n",
    "                       \"New cases per day\":new_cases_perday_southKorea,\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Korea, South\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Korea, South\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Korea, South\",:].tolist()})\n",
    "singapore_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Singapore\",:].index.tolist(),\\\n",
    "                       \"New cases per day\":new_cases_perday_singapore,\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Singapore\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Singapore\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Singapore\",:].tolist()})\n",
    "iran_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Iran\",:].index.tolist(),\\\n",
    "                       \"New cases per day\":new_cases_perday_iran,\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Iran\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Iran\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Iran\",:].tolist()})\n",
    "italy_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Italy\",:].index.tolist(),\\\n",
    "                       \"New cases per day\":new_cases_perday_italy,\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Italy\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Italy\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Italy\",:].tolist()})\n",
    "japan_df=pd.DataFrame({\"Dates\":Confirmed_final.loc[\"Japan\",:].index.tolist(),\\\n",
    "                       \"New cases per day\":new_cases_perday_japan,\\\n",
    "                           \"#Cumulative Confirmed Cases\":Confirmed_final.loc[\"Japan\",:].tolist(),\\\n",
    "                           \"#Cumulative Death Cases\":Deaths_final.loc[\"Japan\",:].tolist(),\n",
    "                           \"#Cumulative Recovered Cases\":Recovered_final.loc[\"Japan\",:].tolist()})\n",
    "#china_df.head()\n",
    "\n",
    "plt.figure(figsize=(15,5))\n",
    "x_axis = np.arange(1, len(china_df)+1)\n",
    "tick_locations_china = []\n",
    "for x in x_axis:\n",
    "    tick_locations_china.append(x)\n",
    "    \n",
    "plt.title(\"Covid-19 new cases per day \")\n",
    "plt.xlabel(\"Period in Days\")\n",
    "plt.ylabel(\"# of cases\")\n",
    "plt.grid()\n",
    "plt.xlim(1,52)\n",
    "    \n",
    "new_cases_perday_china, = plt.plot(x_axis, china_df.loc[:,'New cases per day'], color=\"black\", label=\"New Confirmed Cases per day in China\")\n",
    "new_cases_perday_US, = plt.plot(x_axis, US_df.loc[:,'New cases per day'], color=\"orange\", label=\"New Confirmed Cases per day in US\")\n",
    "new_cases_perday_canada, = plt.plot(x_axis, canada_df.loc[:,'New cases per day'], color=\"magenta\", label=\"New Confirmed Cases per day in Canada\")\n",
    "new_cases_perday_southKorea, = plt.plot(x_axis, southKorea_df.loc[:,'New cases per day'], color=\"cyan\", label=\"New Confirmed Cases per day in South Korea\")\n",
    "new_cases_perday_singapore, = plt.plot(x_axis, singapore_df.loc[:,'New cases per day'], color=\"red\", label=\"New Confirmed Cases per day in Singapore\")\n",
    "new_cases_perday_iran, = plt.plot(x_axis, iran_df.loc[:,'New cases per day'], color=\"green\", label=\"New Confirmed Cases per day in Iran\")\n",
    "new_cases_perday_italy, = plt.plot(x_axis, italy_df.loc[:,'New cases per day'], color=\"blue\", label=\"New Confirmed Cases per day in Italy\")\n",
    "new_cases_perday_japan, = plt.plot(x_axis, japan_df.loc[:,'New cases per day'], color=\"yellow\", label=\"New Confirmed Cases per day in Japan\")\n",
    "\n",
    "plt.legend(handles=[new_cases_perday_china,new_cases_perday_US,new_cases_perday_canada,new_cases_perday_southKorea,new_cases_perday_singapore,new_cases_perday_iran,new_cases_perday_italy,new_cases_perday_japan,], loc=\"upper left\")\n",
    "plt.xticks(tick_locations_china)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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